Device deployment method, device deployment apparatus, electronic device, and storage medium

Abstract

The present disclosure provides a device deployment method, a device deployment apparatus, an electronic device and a storage medium, and relates to the technical field of artificial intelligence and Internet of Things. The method comprises the following steps: determining device indexes and configuration information corresponding to a target device according to a deployment strategy of the target device, wherein the device indexes comprise a first static index value and a first dynamic index value; calculating an index value of each idle site in a target area according to the first static index value, the configuration information, a second static index value corresponding to the target area and position information; determining N candidate sites in the target area based on the index value, wherein N is greater than or equal to 2; generating N dynamic simulation schemes corresponding to the N candidate sites according to the first static index value, the first dynamic index value, the configuration information, a second dynamic index value corresponding to the target area and the position information; and determining a target site from the N candidate sites according to the N dynamic simulation schemes, so as to deploy the target device on the target site.

Description

Technical Field

[0001] This disclosure relates to the fields of artificial intelligence and the Internet of Things, specifically to a device deployment method, device deployment apparatus, electronic device, and storage medium. Background Technology

[0002] For application scenarios involving the deployment of computer equipment, business personnel determine the deployment locations within the data center based on their experience. After the equipment deployment is complete, the locations are adjusted by monitoring actual operational conditions. During the adjustment process, the experience of the business personnel is relied upon to identify and resolve issues in order to optimize the equipment deployment locations.

[0003] However, the aforementioned equipment location adjustment plan is a post-assessment method, which suffers from technical problems such as long adjustment time and low efficiency. Furthermore, the process of adjusting equipment deployment locations requires continuous evaluation and adjustment using both human and computer resources, leading to resource waste. Summary of the Invention

[0004] In view of the above problems, this disclosure provides a device deployment method, a device deployment apparatus, an electronic device, and a storage medium.

[0005] According to a first aspect of this disclosure, a device deployment method is provided, comprising:

[0006] Based on the deployment strategy of the target device, determine the device indicators and configuration information corresponding to the target device. The device indicators include the first static indicator value and the first dynamic indicator value.

[0007] Based on the first static indicator value, configuration information, the second static indicator value corresponding to the target area, and location information, calculate the indicator value of each idle machine position in the target area. The idle machine positions are used to place the target equipment.

[0008] Based on the indicator values, N alternative shooting locations are determined within the target area, where N≥2;

[0009] Based on the first static indicator value, the first dynamic indicator value, configuration information, the second dynamic indicator value corresponding to the target area, and location information, generate N dynamic simulation schemes corresponding to N candidate camera positions; and

[0010] Based on N dynamic simulation schemes, the target location is determined from N candidate locations so that the target equipment can be deployed at the target location.

[0011] According to embodiments of this disclosure, the first static index value includes a first static space index value, a first static power consumption index value, and a first static heat dissipation index value; the configuration information includes the device model; the second static index value includes a second static space index value, a second static power consumption index value, and a second static heat dissipation index value; and the location information includes location coordinates.

[0012] According to embodiments of this disclosure, the calculation of the indicator value for each available server position within the target area based on a first static indicator value, configuration information, a second static indicator value corresponding to the target area, and location information includes:

[0013] The calculated value of the static spatial index is determined based on the comparison relationship between the first static spatial index value and the second static spatial index value.

[0014] The calculated value of the static power consumption index is determined based on the comparison relationship between the first static power consumption index value and the second static power consumption index value.

[0015] The calculated value of the static heat dissipation index is determined based on the sum of the first static heat dissipation index value and the second static heat dissipation index value.

[0016] Based on the equipment model and location coordinates, the environmental readiness time is determined. The environmental readiness time represents the time required to complete the deployment of the target equipment; and

[0017] The index values ​​are determined based on the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and the time required for the environment to be in place.

[0018] According to embodiments of this disclosure, determining the environmental arrival time based on the device model and location coordinates includes:

[0019] Based on the location coordinates, determine the current configuration information and environment preparation time of the available machine slots. The environment preparation time represents the basic time required to deploy the equipment.

[0020] Based on the current configuration information and equipment model, determine the environment adjustment duration. The environment adjustment duration represents the time required to adjust the environment of idle workstations to meet the requirements of the equipment model; and

[0021] The environmental readiness time is determined based on the environmental preparation time and environmental adjustment time.

[0022] According to embodiments of this disclosure, the determination of indicator values ​​based on calculated static space indicators, calculated static power consumption indicators, calculated static heat dissipation indicators, and environmental availability time includes:

[0023] Obtain the longest device installation duration in the service level agreement. The service level agreement includes multiple device models, and each device model corresponds to multiple device installation durations.

[0024] Calculate the difference between the longest equipment installation time and the longest environmental availability time; and

[0025] The product of the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and the difference is used as the index value.

[0026] According to embodiments of this disclosure, the calculation of the indicator value for each available server position within the target area based on a first static indicator value, configuration information, a second static indicator value corresponding to the target area, and location information further includes:

[0027] Determine the position adjustment coefficient based on the position coordinates and position configuration strategy;

[0028] Determine the quantity adjustment coefficient based on the equipment model and quantity configuration strategy;

[0029] The total adjustment coefficient is determined based on the position adjustment coefficient and / or quantity adjustment coefficient; and

[0030] The index values ​​are determined based on the total adjustment coefficient, the calculated values ​​of static space index, the calculated values ​​of static power consumption index, the calculated values ​​of static heat dissipation index, and the environmental arrival time.

[0031] According to embodiments of this disclosure, the configuration information further includes a configuration start time, the dynamic simulation scheme includes resource dynamic change information, the first dynamic index value includes a first dynamic power consumption index value, and the second dynamic index value includes a second dynamic power consumption index value and a dynamic heat dissipation index value.

[0032] Based on the first static indicator value, the first dynamic indicator value, configuration information, the second dynamic indicator value corresponding to the target area, and location information, N dynamic simulation schemes corresponding to N candidate camera positions are generated, including:

[0033] The environmental arrival time is obtained, which is determined based on the location coordinates and device model.

[0034] Determine the ordered time sequence based on the configuration start time and the time required for the environment to be in place;

[0035] By processing the first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value using ordered time series, a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence conforming to ordered time series are obtained; and

[0036] Based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence, dynamic resource change information is generated.

[0037] According to embodiments of this disclosure, resource dynamic change information is generated based on a first static heat dissipation index value, a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence, including:

[0038] The calculated value of the dynamic power consumption index is determined based on the first dynamic power consumption index sequence and the second dynamic power consumption index sequence;

[0039] Based on the first static heat dissipation index value and the dynamic heat dissipation index sequence, determine the calculated value of the dynamic heat dissipation index; and

[0040] Based on the calculated values ​​of static space index, dynamic power consumption index, and dynamic heat dissipation index, information on dynamic changes in resources is generated.

[0041] According to embodiments of this disclosure, the method further includes:

[0042] The dynamic simulation solution is displayed on a visualization page of the target terminal device. The visualization page includes a time scale, which allows users to obtain the dynamic changes of resources at multiple points in time by operating the time scale. The time scale is determined based on an ordered time series.

[0043] According to embodiments of this disclosure, determining the target camera position from N candidate camera positions based on N dynamic simulation schemes includes:

[0044] Based on the dynamic resource change information corresponding to N candidate locations, the target location is determined from the N candidate locations.

[0045] According to embodiments of this disclosure, the dynamic simulation scheme includes a position view;

[0046] Based on the first static indicator value, the first dynamic indicator value, configuration information, the second dynamic indicator value corresponding to the target area, and location information, N dynamic simulation schemes corresponding to N candidate machine positions are generated, which also includes:

[0047] Obtain a 3D view of the target area and the target location coordinates of the alternative camera positions; and

[0048] At the target location coordinates in the 3D view, a preset identifier corresponding to the device model is generated to obtain the location view.

[0049] A second aspect of this disclosure provides an equipment deployment apparatus, comprising:

[0050] The first determining module is used to determine the equipment indicators and configuration information corresponding to the target equipment according to the deployment strategy of the target equipment. The equipment indicators include a first static indicator value and a first dynamic indicator value.

[0051] The calculation module is used to calculate the index value of each idle machine position in the target area based on the first static index value, configuration information, the second static index value corresponding to the target area, and location information. The idle machine positions are used to place the target equipment.

[0052] The second determining module is used to determine N alternative locations within the target area based on the indicator values, where N≥2;

[0053] The simulation calculation module is used to generate N dynamic simulation schemes corresponding to N candidate camera positions based on the first static index value, the first dynamic index value, configuration information, the second dynamic index value corresponding to the target area, and location information; and

[0054] The third determination module is used to determine the target location from N candidate locations based on N dynamic simulation schemes, so as to deploy the target equipment at the target location.

[0055] A third aspect of this disclosure provides an electronic device comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to perform the device deployment method described above.

[0056] A fourth aspect of this disclosure also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the above-described device deployment method.

[0057] The fifth aspect of this disclosure also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described device deployment method.

[0058] In this embodiment, an index value is calculated using a first static index value of the target device and a second static index value of the target area for preliminary screening. N candidate locations are determined from multiple available locations, achieving preliminary screening of deployment locations from a static perspective, which reduces the difficulty of index calculation and improves computational efficiency. A second dynamic index value is used to further determine the target location from the multiple candidate locations, achieving secondary screening of deployment locations from a dynamic perspective, which further improves the accuracy of target location selection. The embodiments of this disclosure, combining static and dynamic resources, enable equipment deployment location planning at different granularities, improving deployment efficiency and reducing computational workload.

[0059] Furthermore, the embodiments of this disclosure predict the operation of the target area from the start of deployment to the completion of deployment through simulation. This allows the detection and adjustment of the target device's operating effect to be carried out in advance at the planning stage, eliminating the need for rework and adjustments after problems occur during actual deployment. This improves deployment efficiency and reduces the waste of deployment resources. Attached Figure Description

[0060] The foregoing contents, as well as other objects, features, and advantages of this disclosure, will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0061] Figure 1 This illustration schematically depicts an application scenario of a device deployment method according to an embodiment of the present disclosure;

[0062] Figure 2 A flowchart illustrating a device deployment method according to an embodiment of the present disclosure is shown schematically.

[0063] Figure 3A A flowchart illustrating a method for calculating index values ​​according to an embodiment of the present disclosure is shown schematically.

[0064] Figure 3B A flowchart illustrating a method for determining dynamic resource change information according to an embodiment of the present disclosure is shown schematically.

[0065] Figure 4 A schematic diagram illustrating dynamic power consumption index values ​​according to a specific embodiment of the present disclosure is shown.

[0066] Figure 5 An architectural diagram of a simulation model according to an embodiment of the present disclosure is illustrated schematically;

[0067] Figure 6 An architectural diagram of a simulation computing module according to an embodiment of the present disclosure is shown schematically;

[0068] Figure 7 A schematic block diagram of a device deployment apparatus according to an embodiment of the present disclosure is shown; and

[0069] Figure 8 A block diagram of an electronic device suitable for a device deployment method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0070] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0071] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0072] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0073] When using expressions such as "at least one of A, B, and C", they should generally be interpreted in accordance with the meaning that is commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B, and C, etc.).

[0074] In the technical solutions disclosed herein, the collection, storage, use, processing, transmission, provision, disclosure, and application of data (including but not limited to user personal information) comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and they do not violate public order and good morals.

[0075] In data center equipment deployment scenarios, different installation locations within the same server room can produce different results for servers with the same configuration. For example, installing the equipment to be deployed directly in an empty rack, while simple and feasible, results in wasted resources due to the increased distance between the equipment and other devices, increasing the need for fiber optic cables and other information transmission media. If installed in a rack where other equipment is already located, improper installation can cause localized hotspots to exceed the rack's power capacity, leading to power outages and impacting equipment operation.

[0076] In the traditional model, the effectiveness of the aforementioned data center resources is generally determined through post-event evaluation. This involves deploying equipment first, then collecting and analyzing data based on actual usage results, and adjusting server locations to resolve issues. The drawback of this approach is the long deployment and server location adjustment process, which is inefficient.

[0077] Furthermore, in the aforementioned post-evaluation methods, the effectiveness of equipment placement adjustments relies on the practical experience of the operational personnel. For large data centers containing tens of thousands of devices, relying solely on the practical experience of operational personnel to optimize equipment deployment locations will result in a massive workload, extremely low adjustment efficiency, and poor adjustment results.

[0078] Embodiments of this disclosure provide a device deployment method, comprising: determining device indicators and configuration information corresponding to the target device according to a deployment strategy for the target device, wherein the device indicators include a first static indicator value and a first dynamic indicator value; calculating the indicator value of each vacant machine position in the target area according to the first static indicator value, configuration information, a second static indicator value corresponding to the target area, and location information, wherein the vacant machine position is used to place the target device; determining N candidate machine positions in the target area based on the indicator values, wherein N≥2; generating N dynamic simulation schemes corresponding to the N candidate machine positions according to the first static indicator value, the first dynamic indicator value, configuration information, the second dynamic indicator value corresponding to the target area, and location information; and determining the target machine position from the N candidate machine positions according to the N dynamic simulation schemes, so as to deploy the target device on the target machine position.

[0079] Figure 1 The illustration schematically depicts an application scenario of a device deployment method according to embodiments of the present disclosure. It should be noted that... Figure 1 The examples shown are merely examples of application scenarios that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0080] like Figure 1 As shown, application scenario 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a server 104, a network 105, a first sensor 106, a second sensor 107, and a third sensor 108. The network 105 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, the server 104, the first sensor 106, the second sensor 107, and the third sensor 108. The network 105 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0081] Users can use at least one of the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 104 to interact with at least one of the first sensor 106, the second sensor 107, and the third sensor 108 via the network 105 to receive or send messages, etc.

[0082] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be equipped with various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (for example only).

[0083] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0084] Server 104 can be a server that provides various services, such as a backend management server that processes the information fed back by the first sensor 106, the second sensor 107, and the third sensor 108 (for example only). The backend management server can analyze and process the received sensor data and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0085] Sensors 106, 107, and 108 can be various sensing devices used to monitor environmental information in the computer room area, such as infrared sensors to detect heat dissipation in the computer room, and pressure sensors to measure the load-bearing capacity of the server racks. Sensors also include power meters, cameras, real-time equipment monitoring components, and other monitoring units with data detection functions implemented through programming.

[0086] It should be noted that the device deployment method provided in this embodiment can generally be executed by the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 104. Correspondingly, the device deployment apparatus provided in this embodiment can generally be located within the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 104. The device deployment method provided in this embodiment can also be executed by a server or server cluster that is different from the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 104 but is capable of communicating with them. Correspondingly, the device deployment apparatus provided in this embodiment can also be located within a server or server cluster that is different from the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 104 but is capable of communicating with them.

[0087] For example, the first static indicator value, the first dynamic indicator value, the second static indicator value, and the second dynamic indicator value can be provided by at least one of sensors 106, 107, and 108, and transmitted to the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or the server 104 (such as the first terminal device 101). Then, the first terminal device 101 can locally execute the device deployment method provided in the embodiments of this disclosure, or send the first static indicator value, the first dynamic indicator value, the second static indicator value, and the second dynamic indicator value to other terminal devices, servers, or server clusters, and have the other terminal devices, servers, or server clusters that receive these indicator information execute the device deployment method provided in the embodiments of this disclosure.

[0088] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0089] It should be noted that the device deployment method, device deployment apparatus, computer system, computer-readable storage medium and computer program product disclosed herein can be used in the fields of artificial intelligence and Internet of Things, as well as in any field other than the fields of artificial intelligence and Internet of Things. The application fields of the device deployment method, device deployment apparatus, computer system, computer-readable storage medium and computer program product disclosed herein are not limited.

[0090] The following will be based on Figure 1 The described scene, through Figures 2-4 The device deployment method of the disclosed embodiments will be described in detail.

[0091] Figure 2 A flowchart illustrating a device deployment method according to an embodiment of the present disclosure is shown schematically.

[0092] like Figure 2 As shown, the method 200 includes operations S210 to S250.

[0093] In operation S210, based on the deployment strategy of the target device, the device indicators and configuration information corresponding to the target device are determined. The device indicators include the first static indicator value and the first dynamic indicator value.

[0094] According to embodiments of this disclosure, the target device includes a server device for acquiring, processing, and transmitting computer information.

[0095] According to embodiments of this disclosure, the deployment strategy takes the form of a work order. Business personnel can obtain a work order through a terminal device and input it into the device deployment system / device, so that the device deployment system / device can determine the target location of the target device to be deployed based on the work order.

[0096] According to embodiments of this disclosure, by analyzing the device specifications of the target device and the regional specifications of the target area, the location of the target device to be deployed can be determined from the target area. The target area is the region of the target area to be deployed.

[0097] According to embodiments of this disclosure, equipment indicators include the index values ​​of standard indicators corresponding to the equipment. Area indicators include the index values ​​of standard indicators corresponding to the area within the data center where the equipment is to be deployed. Standard indicators include: space indicators, power consumption indicators, and heat dissipation indicators.

[0098] According to embodiments of this disclosure, for a device, space metrics include the device's weight and physical space (in units of U); power consumption metrics include the device's power consumption; and heat dissipation metrics include the device's heat dissipation performance.

[0099] For a given area, spatial metrics include the load-bearing capacity and physical space occupied by each rack within the area; power consumption metrics include the power consumption of each rack within the area; and heat dissipation metrics include the overall heat dissipation of the area.

[0100] According to embodiments of this disclosure, configuration information is used to characterize the hardware configuration information of the target device, including the number of interfaces, device type, etc.

[0101] According to embodiments of this disclosure, the first static index value of the target device is a single fixed value, representing the average value of the device index within a preset time period; the first dynamic index value is related to the device's operating period and operating load, and is a dynamic fluctuation curve.

[0102] For example, regarding power consumption indicators, the first static indicator value includes the average power consumption of the device, and the first dynamic indicator value includes the fluctuation pattern of the device power over time and with load.

[0103] In operation S220, the indicator value of each idle machine position in the target area is calculated based on the first static indicator value, configuration information, the second static indicator value corresponding to the target area, and location information.

[0104] According to embodiments of this disclosure, the target area can be defined as a data center, a server rack, or a floor. The target area includes multiple vacant server positions and multiple occupied server positions, where an occupied server position indicates that equipment has already been deployed there. Vacant server positions can be used to deploy the target equipment.

[0105] According to embodiments of this disclosure, the location information corresponding to the target area includes the location information of multiple cabinets within the target area and multiple rack positions within each cabinet.

[0106] According to embodiments of this disclosure, the second static index value is a single fixed value corresponding to the regional index within the target area, representing the average situation of the regional index of the target area within a preset time period.

[0107] According to embodiments of this disclosure, the index value characterizes the utilization of data center resources within a target area. For example, a higher index value indicates higher utilization efficiency of data center resources, while a lower index value indicates lower utilization efficiency of data center resources.

[0108] By combining the first static index value and configuration information of the target device with the second static index value and location information of the target area, the index value after deploying the target device in any available location within the target area can be calculated, so as to characterize whether the available location is the optimal deployment location for the target device through the index value.

[0109] In operation S230, based on the indicator value, N alternative camera positions are determined within the target area, where N≥2.

[0110] According to embodiments of this disclosure, after calculating the index value of each available camera position in the target area, N candidate camera positions are determined from multiple available camera positions in the target area if the index value meets preset conditions.

[0111] For example, the available indicator values ​​can be arranged in descending order, and N indicator values ​​can be selected sequentially from the largest indicator value in the direction of decreasing indicator value. The N available camera positions corresponding to the N indicator values ​​are then determined as N candidate camera positions.

[0112] In operation S240, based on the first static index value, the first dynamic index value, configuration information, the second dynamic index value corresponding to the target area, and the location information, N dynamic simulation schemes corresponding to N alternative machine positions are generated.

[0113] According to embodiments of this disclosure, after determining N candidate server locations from multiple available server locations in the target area, for each of the N candidate server locations, a simulation model is used to simulate and calculate the dynamic changes of data center resources from the start of deployment to the completion of deployment, generating N dynamic simulation schemes, so as to determine an optimal target server location based on the dynamic simulation schemes.

[0114] According to embodiments of this disclosure, the input to the simulation model may include: a first static indicator value, a first dynamic indicator value, and configuration information of the target device, and a second dynamic indicator value and location information of the target area. The simulation model predicts the dynamic changes of resources in the target area over a future period based on the input. This future period includes three stages: pre-deployment, during deployment, and post-deployment.

[0115] When operating the S250, the target location is determined from N alternative locations based on N dynamic simulation schemes, so that the target equipment can be deployed at the target location.

[0116] According to embodiments of this disclosure, during actual operation, the device indicators of the target device will change with time and device load. Therefore, during the deployment of the target device, the device indicators are not fixed. By using information such as the first static indicator value, the first dynamic indicator value of the target device, and the second dynamic indicator value of the target area, the specific changes in the candidate device locations can be simulated in the time dimension to determine the optimal deployment location.

[0117] In this embodiment, an index value is calculated using a first static index value of the target device and a second static index value of the target area for preliminary screening. N candidate locations are determined from multiple available locations, achieving preliminary screening of deployment locations from a static perspective, which reduces the difficulty of index calculation and improves computational efficiency. A second dynamic index value is used to further determine the target location from the multiple candidate locations, achieving secondary screening of deployment locations from a dynamic perspective, which further improves the accuracy of target location selection. The embodiments of this disclosure, combining static and dynamic resources, enable equipment deployment location planning at different granularities, improving deployment efficiency and reducing computational workload.

[0118] Furthermore, the embodiments of this disclosure predict the operation of the target area from the start of deployment to the completion of deployment through simulation. This allows the detection and adjustment of the target device's operating effect to be carried out in advance at the planning stage, eliminating the need for rework and adjustments after problems occur during actual deployment. This improves deployment efficiency and reduces the waste of deployment resources.

[0119] According to embodiments of this disclosure, the first static index value includes a first static space index value, a first static power consumption index value, and a first static heat dissipation index value; the configuration information includes the device model; the second static index value includes a second static space index value, a second static power consumption index value, and a second static heat dissipation index value; and the location information includes location coordinates.

[0120] According to embodiments of this disclosure, the indicator value of each available machine position in the target area is calculated based on a first static indicator value, configuration information, a second static indicator value corresponding to the target area, and location information, including the following steps.

[0121] The calculated value of the static spatial index is determined based on the comparison between the first static spatial index value and the second static spatial index value.

[0122] The calculated value of the static power consumption index is determined based on the comparison between the first static power consumption index value and the second static power consumption index value.

[0123] The calculated value of the static heat dissipation index is determined based on the sum of the first static heat dissipation index value and the second static heat dissipation index value.

[0124] Based on the equipment model and location coordinates, determine the environmental arrival time, which represents the time required to complete the deployment of the target equipment.

[0125] The index values ​​are determined based on the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and the time required for the environment to be in place.

[0126] According to embodiments of this disclosure, the static space index calculation value characterizes whether the target device can be installed in a certain vacant machine position in the computer room in terms of physical space dimension.

[0127] According to embodiments of this disclosure, the first static space index value includes equipment specifications, which can be determined by a manufacturer's measurement label on the target equipment. The second static space index value includes remaining rack space. The comparison between the first and second static space index values ​​includes whether the equipment specifications are less than the remaining rack space.

[0128] For example, if the remaining space in the rack is greater than the equipment specifications, it means that the rack can physically support the target equipment, and the corresponding static space index is calculated to be 1. Conversely, if the remaining space in the rack is less than or equal to the equipment specifications, it means that the rack will be overloaded after carrying the target equipment, which poses a risk of the rack collapsing, and the static space index is calculated to be 0.

[0129] According to embodiments of this disclosure, the static power consumption index calculation value characterizes whether the target device can be installed in a vacant machine slot in the computer room in terms of power consumption.

[0130] According to embodiments of this disclosure, the first static power consumption indicator value includes the average power consumption (or average power usage) of the target device, which can be determined based on historical measurement results of devices of the same type or purpose. The second static space indicator value includes the remaining power of the rack. The comparison between the first static power consumption indicator value and the second static power consumption indicator value includes whether the average power consumption is less than the remaining power of the rack.

[0131] For example, if the remaining power of the cabinet is greater than the average power, it means that the cabinet can support the target equipment in terms of power consumption standards, and the corresponding static power consumption index is calculated as 1. Conversely, if the remaining power of the cabinet is less than or equal to the average power, it means that the power consumption of the cabinet will exceed the power consumption specifications after supporting the target equipment, which makes the power socket of the cabinet at risk of overload operation. In this case, the static power consumption index is calculated as 0.

[0132] According to embodiments of this disclosure, the static heat dissipation index calculation value characterizes whether the target device can be installed in a vacant machine slot in the computer room in terms of heat dissipation dimension.

[0133] According to embodiments of this disclosure, taking a typical under-rack air-conditioning server room as an example, all the cooling energy for the server racks originates from beneath the floor. Therefore, equipment located under the server racks not only receives cooling energy more easily from the air conditioning system, resulting in better heat dissipation, but also experiences less heat loss due to the shorter cooling conduction distance, leading to higher cooling efficiency and greater utilization of server room resources. Thus, based on the location of the target equipment within the server rack, a first static heat dissipation index value can be determined.

[0134] For example, taking a 6-layer server rack as an example, the first static heat dissipation index value of the equipment deployed in the bottom space of the rack is 1.5, and the values ​​for the equipment deployed in the top layer are 1.3, 1.2, 1.1, 1.0 and 0.8 respectively. The specific distribution of the first static heat dissipation index value can be used according to the server rack heat dissipation model.

[0135] According to embodiments of this disclosure, the second heat dissipation index value characterizes the static heat dissipation information of the target area, taking into account that the heat dissipation of the target area changes with time, season, and other information. Therefore, when calculating the static heat dissipation index value, the second heat dissipation index value can be the average heat dissipation during the daytime in the current season, and can be used with a regional heat dissipation model.

[0136] According to the embodiments of this disclosure, the deployment planning of the data center needs to take into account the time factor, and needs to combine the time when the equipment can be put into use to determine whether a certain idle position is the most suitable position.

[0137] According to embodiments of this disclosure, the environmental availability time characterizes the time required to complete the deployment of the target device.

[0138] According to embodiments of this disclosure, determining the environmental arrival time based on the device model and location coordinates includes the following steps.

[0139] Based on the location coordinates, determine the current configuration information and environment preparation time of the available machine slots. The environment preparation time represents the basic time required to deploy the equipment.

[0140] Based on the current configuration information and equipment model, determine the environment adjustment duration. The environment adjustment duration represents the time required to adjust the environment of the idle machine slots to meet the requirements of the equipment model.

[0141] The environmental readiness time is determined based on the environmental preparation time and environmental adjustment time.

[0142] According to embodiments of this disclosure, environment preparation time refers to the time required for each department in the data center to deploy a device, and the environment preparation time is the same for all machine positions.

[0143] According to embodiments of this disclosure, the current configuration information represents the current network resource configuration of the idle machine slot, including whether fiber optic cables and network cables are configured and the quantity configured.

[0144] According to embodiments of this disclosure, the configuration of each vacant server position is different. For example, vacant server position A is already equipped with a network cable, while vacant server position B is not equipped with a network cable.

[0145] Different device models require different environmental resources. For example, device model C requires one network cable, while device model D requires two network cables. Therefore, multiple device models and coordinate locations correspond to multiple environmental setup times. Thus, the environmental setup time can be determined based on the device model and the current configuration information of available server positions.

[0146] For example, for the second installation position in the first row (1, 2), the current configuration information is 1 network cable configured, with no fiber optic cable configured. The target device for device model A requires 2 network cables and 3 fiber optic cables, while the target device for device model B requires 1 network cable and 3 fiber optic cables. Therefore, the environmental setup time for device model B is shorter than that for device model A, resulting in a shorter environmental availability time for device model B compared to device model A.

[0147] According to embodiments of this disclosure, after determining the calculated values ​​of static space indicators, static power consumption indicators, static heat dissipation indicators, and environmental availability time, the indicator values ​​for a certain idle machine slot can be determined based on the above information.

[0148] In the embodiments of this disclosure, since deployment time also affects deployment efficiency, when determining whether each idle location is the most suitable location, not only static resources such as space, power consumption, and heat dissipation are considered, but the time when the equipment can be put into place and used is also creatively taken into account. At the same time, location planning in both spatial and temporal dimensions can improve the accuracy of location deployment.

[0149] According to embodiments of this disclosure, determining indicator values ​​based on calculated static space indicators, calculated static power consumption indicators, calculated static heat dissipation indicators, and environmental availability time includes the following steps:

[0150] Obtain the longest device installation duration in the Service Level Agreement (SLA). The SLA includes multiple device models, and each device model corresponds to multiple device installation durations.

[0151] Calculate the difference between the longest equipment installation time and the longest time for the environment to be in place.

[0152] The product of the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and the difference is used as the index value.

[0153] According to embodiments of this disclosure, a Service-Level Agreement (SLA) is an agreement between a network service provider and a customer that defines the type of service, quality of service, and customer payment terms. The SLA includes multiple device models, each corresponding to multiple device installation durations.

[0154] According to the embodiments of this disclosure, the static space index is calculated as X, the static power consumption index is calculated as Y, the static heat dissipation index is calculated as Z, the environmental arrival time is calculated as T, and the longest equipment installation time is determined as N. The index value of the idle machine space can be calculated based on X, Y, Z, T, and N.

[0155] The process of calculating the index value follows the formula:

[0156] P(a,b)=X*Y*Z*(NT) (1)

[0157] Wherein, P(a,b) represents the index value of the available machine slots in the a-th row and the b-th installation position.

[0158] The embodiments of this disclosure can better determine alternative locations by comparing the time it takes for the environment to arrive with the time it took for the equipment to be installed previously, taking historical factors into account.

[0159] According to embodiments of this disclosure, the method for calculating the index value of each available machine position within the target area based on a first static index value, configuration information, a second static index value corresponding to the target area, and location information further includes the following steps.

[0160] Determine the position adjustment coefficient based on the position coordinates and position configuration strategy.

[0161] Determine the quantity adjustment coefficient based on the equipment model and quantity configuration strategy.

[0162] The total adjustment coefficient is determined based on the position adjustment coefficient and / or the quantity adjustment coefficient.

[0163] The index values ​​are determined based on the total adjustment coefficient, the calculated values ​​of static space index, the calculated values ​​of static power consumption index, the calculated values ​​of static heat dissipation index, and the environmental arrival time.

[0164] According to embodiments of this disclosure, the location configuration strategy represents an adjustment strategy based on the location of available workstations, and the quantity configuration strategy represents an adjustment strategy based on the number of workstations. According to embodiments of this disclosure, the location configuration strategy and the quantity configuration strategy can be obtained from a configuration library in real time.

[0165] According to embodiments of this disclosure, the location configuration strategy includes: for multiple server racks, prioritizing the placement of racks with fewer available racks.

[0166] For example, available server slot A is (1, 1, 2), representing the second server slot in the first row of the first rack; available server slot B is (2, 1, 2), representing the second server slot in the first row of the second rack. Since there are 3 available server slots in the first rack and 5 available server slots in the second rack, the position adjustment factor for available server slot A is greater than that for available server slot B.

[0167] According to embodiments of this disclosure, the location configuration strategy further includes: prioritizing the placement of generator positions with abundant equipment resources.

[0168] For example, vacant server position A is located at (1, 1, 2) and is equipped with one network cable and one fiber optic cable; vacant server position B is located at (2, 1, 2) and is equipped with one network cable. The position adjustment factor of vacant server position A is greater than that of vacant server position B.

[0169] According to embodiments of this disclosure, the location configuration strategy further includes prioritizing locations that are not under maintenance. When a location is under maintenance, the installation of the target device cannot begin until the maintenance is complete, resulting in wasted waiting time and impacting configuration efficiency. Therefore, the location adjustment coefficient for locations not under maintenance is greater than that for locations under maintenance.

[0170] According to embodiments of this disclosure, the quantity configuration strategy includes prioritizing the installation of the device type with the largest quantity.

[0171] For example, when the device type of the first target device is X, since the number of devices of device type X is the largest in the entire computer room, the quantity adjustment coefficient of the first target device is greater than that of the second target device of device type Y.

[0172] According to embodiments of this disclosure, the position adjustment coefficient or the quantity adjustment coefficient can be determined as the total adjustment coefficient; or the product of the position adjustment coefficient and the quantity adjustment coefficient can be used as the total adjustment coefficient.

[0173] According to embodiments of this disclosure, the process of determining the index values ​​based on the total adjustment coefficient, the calculated value of the static space index, the calculated value of the static power consumption index, the calculated value of the static heat dissipation index, and the environmental arrival time satisfies the following formula:

[0174] P(a,b)=K*X*Y*Z*(NT) (2)

[0175] Where K represents the total adjustment coefficient, the calculated value of the static space index is X, the calculated value of the static power consumption index is Y, the calculated value of the static heat dissipation index is Z, the environmental arrival time is T, and the longest equipment installation time is N.

[0176] Since deployment time also affects deployment efficiency, the embodiments of this disclosure not only consider space, power consumption, heat dissipation, and time, but also actual factors such as the actual maintenance of the data center and the placement of server racks. The total adjustment coefficient is determined through location configuration strategy and / or quantity configuration strategy, so as to flexibly and realistically determine the alternative server locations and improve the accuracy of determining the target server locations.

[0177] Figure 3A A flowchart illustrating a method for calculating index values ​​according to an embodiment of the present disclosure is shown.

[0178] like Figure 3A As shown, application scenario 300A includes the process of determining the indicator value using the first static indicator value, the second static indicator value, location information, and configuration information.

[0179] According to embodiments of this disclosure, the first static index value of the target device includes a first static space index value 3201, a first static power consumption index value 3203, and a first static heat dissipation index value 3205, and the configuration information includes a device model 3207.

[0180] According to embodiments of this disclosure, the second static index value of the target area includes a second static space index value 3202, a second static power consumption index value 3204, and a second static heat dissipation index value 3208, and the location information includes location coordinates 3208.

[0181] Based on the first static space index value 3201 and the second static space index value 3202, the calculated value of the static space index 3209 is determined.

[0182] Based on the first static power consumption index value 3203 and the second static power consumption index value 3204, the calculated static power consumption index value 3210 is determined.

[0183] Based on the first static heat dissipation index value 3205 and the second static heat dissipation index value 3206, the calculated value of the static heat dissipation index is determined to be 3211.

[0184] Based on the equipment model 3207 and location coordinates 3208, the environmental waiting time is determined to be 3212.

[0185] Based on the calculated values ​​of static space index 3209, static power consumption index 3210, static heat dissipation index 3211, and environmental waiting time 3212, the index value 3213 is determined.

[0186] As another specific embodiment of this disclosure, the quantity adjustment coefficient can be determined based on the device model 3207, the position adjustment coefficient can be determined based on the position coordinates, and the total adjustment coefficient can be determined based on the quantity adjustment coefficient and / or the position adjustment coefficient. Based on the total adjustment coefficient, the static space index calculation value 3209, the static power consumption index calculation value 3210, the static heat dissipation index calculation value 3211, and the environmental waiting time 3212, the index value 3213 is determined.

[0187] According to embodiments of this disclosure, the dynamic simulation scheme includes information on dynamic changes in resources.

[0188] The configuration information also includes the configuration start time, the first dynamic indicator value including the first dynamic power consumption indicator value, and the second dynamic indicator value including the second dynamic power consumption indicator value and the dynamic heat dissipation indicator value.

[0189] Based on the first static index value, the first dynamic index value, configuration information, the second dynamic index value corresponding to the target area, and location information, generate N dynamic simulation schemes corresponding to N alternative machine positions, including the following steps.

[0190] The environmental arrival time is obtained, which is determined based on the location coordinates and device model.

[0191] Determine the ordered time sequence based on the configuration start time and the time required for the environment to be in place;

[0192] By processing the first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value using ordered time series, a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence conforming to ordered time series are obtained; and

[0193] Based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence, dynamic resource change information is generated.

[0194] According to embodiments of this disclosure, the environmental arrival time can be determined during the calculation of the aforementioned indicator values ​​and stored as a mandatory parameter. Alternatively, the environmental arrival time can be obtained directly.

[0195] According to embodiments of this disclosure, the environmental arrival time can also be determined again based on location coordinates and device model. The specific determination process is similar to the process described above and will not be repeated here.

[0196] According to embodiments of this disclosure, after determining the configuration start time and the environment availability duration, an ordered time series that varies over time can be generated starting from the configuration start time. This ordered time series includes three time periods: a pre-deployment phase, a deployment phase, and a post-deployment phase. The duration of the deployment phase is equal to the environment availability duration, the duration of the pre-deployment phase is a first preset duration, and the duration of the post-deployment phase is a second preset duration. The first and second preset durations can be determined based on actual conditions; for example, the first preset duration may be one-third of the environment availability duration, and the second preset duration may also be one-third of the environment availability duration.

[0197] According to embodiments of this disclosure, by using an ordered time series including three time periods, the dynamic changes of resources in the entire target area from before deployment to during deployment and from during deployment to after deployment can be generated, clearly and explicitly representing the impact of the use of the alternative server location on the entire data center, thereby more accurately determining the target server location based on dynamic information.

[0198] According to embodiments of this disclosure, the first dynamic power consumption index, the second dynamic power consumption index, and the dynamic heat dissipation index can be dynamic change curves / patterns of power consumption and heat dissipation within 24 hours or over four seasons.

[0199] According to embodiments of this disclosure, processing the first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value using an ordered time series includes: selecting a time period that matches the ordered time series from the first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value, and determining the index value corresponding to the time period to form a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence that conform to the ordered time series.

[0200] According to embodiments of this disclosure, the heat dissipation of the target device fluctuates very little, but the heat dissipation of the target area is related to factors such as the internal and external environment of the computer room and weather. Therefore, in the process of generating dynamic resource change information, the dynamic heat dissipation of the target area is determined based on the first static heat dissipation index value of the target device and the dynamic heat dissipation index sequence of the target area. Then, dynamic resource change information is generated based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence.

[0201] The embodiments of this disclosure generate an ordered time series and, based on multiple indicators, generate a simulation scheme, which can determine the simulated changes in the data center resources within the ordered time series, helping to more accurately determine the target data center from the candidate data centers.

[0202] According to embodiments of this disclosure, resource dynamic change information is generated based on a first static heat dissipation index value, a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence, including the following steps.

[0203] The calculated value of the dynamic power consumption index is determined based on the first dynamic power consumption index sequence and the second dynamic power consumption index sequence;

[0204] Based on the first static heat dissipation index value and the dynamic heat dissipation index sequence, determine the calculated value of the dynamic heat dissipation index; and

[0205] Based on the calculated values ​​of static space index, dynamic power consumption index, and dynamic heat dissipation index, information on dynamic changes in resources is generated.

[0206] According to embodiments of this disclosure, both the first dynamic power consumption index sequence and the second dynamic power consumption index sequence are based on an ordered time series. At any given time point, the power consumption index value at that time point in the second dynamic power consumption index sequence is subtracted from the power consumption index value at that time point in the first dynamic power consumption index sequence to obtain the calculated dynamic power consumption index value at that time point, thereby generating a calculated dynamic power consumption index value based on an ordered time series.

[0207] According to an embodiment of this disclosure, the first static heat dissipation index value is fixed. Therefore, the dynamic heat dissipation index at each moment in the dynamic heat dissipation index sequence can be increased by the first static heat dissipation index value to obtain a dynamic heat dissipation index calculation value that conforms to an ordered time sequence.

[0208] According to embodiments of this disclosure, generating information on dynamic resource changes based on calculated static space index values, calculated dynamic power consumption index values, and calculated dynamic heat dissipation index values ​​includes the following steps:

[0209] At each moment of the ordered time series, the index value at that moment is calculated according to formula (1). After determining the index value at each moment in the ordered time series, dynamic resource change information can be generated according to the ordered time series.

[0210] Figure 3B A flowchart illustrating a method for determining dynamic resource change information according to an embodiment of this disclosure is shown.

[0211] like Figure 3B As shown, application scenario 300B includes the process of generating dynamic resource change information based on a first static indicator value, a first dynamic indicator value, configuration information, a second dynamic indicator value, and location information.

[0212] According to an embodiment of this disclosure, the environmental waiting time 3212 is determined based on the device model 3207 and the location coordinates 3208.

[0213] Based on the environmental arrival time 3212 and the configuration start time 3401, an ordered time series 3403 can be determined. Using the ordered time series 3403, the first dynamic power consumption index value 3402, the second dynamic power consumption index value 3404, and the dynamic heat dissipation index value 3405 are processed respectively to obtain the first dynamic power consumption index sequence 3406, the second dynamic power consumption index sequence 3407, and the dynamic heat dissipation index sequence 3408.

[0214] By comparing the first dynamic power consumption index sequence 3406 and the second dynamic power consumption index sequence 3407, the dynamic power consumption index value 3410 can be calculated.

[0215] By comparing the first static heat dissipation index value 3409 and the dynamic heat dissipation index sequence 3408, the calculated value of the dynamic heat dissipation index 3411 is obtained.

[0216] Based on the calculated static space index value 3209, the dynamic power consumption index value 3410, and the calculated dynamic heat dissipation index value 3411, dynamic resource change information 3412 is generated.

[0217] According to embodiments of this disclosure, the first dynamic power consumption value is related to the device load and the device usage time.

[0218] Figure 4 A schematic diagram illustrating dynamic power consumption index values ​​according to a specific embodiment of the present disclosure is shown.

[0219] like Figure 4 As shown, application scenario 400 is a schematic diagram illustrating the power change of the same device over time under high load and low load conditions.

[0220] like Figure 4 As stated, under high load conditions, the power consumption of the equipment is higher than that under low load conditions. Between 10:00 and 24:00, the power consumption of the equipment under high load conditions fluctuates around 0.6 kW, while under low load conditions it fluctuates around 0.5 kW. Between 00:00 and 10:00, the power consumption of the equipment under high load conditions fluctuates around 0.525 kW, while under low load conditions it fluctuates around 0.475 kW.

[0221] Therefore, the power consumption under high load conditions is higher than that under low load conditions; the power consumption during the period from 10:00 to 24:00 is greater than that during the period from 00:00 to 10:00.

[0222] According to embodiments of this disclosure, a first dynamic power consumption value can be determined based on actual power consumption detection data. For example, a baseline (such as 0.6 kW, 0.5 kW, 0.525 kW, 0.475 kW) can be processed by a 20% variation coefficient to obtain a varying first dynamic power consumption value.

[0223] It should be noted that in related technologies, power consumption can be determined through a power distribution unit (PDU), also known as a rack power distribution socket. However, in this application, since the first dynamic power consumption value changes with time, the PDU cannot detect the change in power consumption over time. Therefore, the dynamic power consumption value can be obtained through a device detection plug-in.

[0224] According to embodiments of this disclosure, after determining the resource dynamic change information corresponding to N candidate locations, the N resource dynamic change information can be displayed on the visualization page of the target terminal device. The visualization page includes a time scale so that users can obtain the resource dynamic change status at multiple times by operating the time scale. The time scale is determined based on an ordered time series.

[0225] According to embodiments of this disclosure, the indicator values ​​of N candidate camera positions can also be displayed on a visualization interface, allowing users to intuitively see the static and dynamic resources of the recommended N candidate camera positions.

[0226] For example, users can drag the time scale within the visualization interface to see how data center resources change over different time periods. It should be noted that the configuration start time is usually after the current time; therefore, the dynamic changes in resources in the target area before, during, and after deployment are all determined by simulation.

[0227] The embodiments disclosed herein can simulate resource changes during the deployment process based on time and space simulations. This not only solves the problem of where to place equipment appropriately, but also extrapolates the usage of infrastructure resources at future selectable time points. This helps in subsequent system risk analysis of data center capacity without the need for remeasurement.

[0228] According to embodiments of this disclosure, a target camera position is determined from N candidate camera positions based on dynamic resource change information corresponding to N candidate camera positions.

[0229] According to embodiments of this disclosure, a candidate camera position with the largest calculated dynamic power consumption index can be selected from N candidate camera positions, and this candidate camera position can be determined as the target camera position.

[0230] According to embodiments of this disclosure, a candidate location with the largest calculated value of dynamic heat dissipation index can be selected from N candidate locations, and this candidate location can be determined as the target location.

[0231] According to embodiments of this disclosure, the dynamic resource change information corresponding to N candidate camera positions can also be transmitted to the target terminal device, and the target camera position can be determined in response to the user's preset operation.

[0232] For example, in response to a user's selection of the nth alternative camera position, the nth alternative camera position is determined as the target camera position, where n is greater than or equal to 1 and n is less than or equal to N.

[0233] The embodiments of this disclosure determine the target camera position based on dynamic changes after determining the candidate camera positions based on static resources. Combining dynamic and static resources can more accurately determine the target camera position.

[0234] According to embodiments of this disclosure, the dynamic simulation scheme includes a position view.

[0235] Based on the first static indicator value, the first dynamic indicator value, configuration information, the second dynamic indicator value corresponding to the target area, and location information, N dynamic simulation schemes corresponding to N candidate machine positions are generated, which also includes:

[0236] Obtain a 3D view of the target area and the target location coordinates of the alternative camera positions; and

[0237] At the target location coordinates in the 3D view, a preset identifier corresponding to the device model is generated to obtain the location view.

[0238] According to embodiments of this disclosure, the dynamic simulation scheme includes resource dynamic change information and location view. Before, after, or simultaneously with determining the resource dynamic change information, the location view corresponding to N candidate machine positions can be determined.

[0239] According to embodiments of this disclosure, a 3D view of the target area can be stored as a template in the simulation model, for example, a template can be formed by computer room. A view of the target device can also be stored as a preset identifier in the simulation model, for example, a cuboid block with text labels.

[0240] According to embodiments of this disclosure, after obtaining a three-dimensional view of the target area, a preset identifier is generated at the target position coordinates corresponding to the N candidate camera positions in the three-dimensional view, so that all N candidate camera positions are displayed in the same three-dimensional view, thereby reducing resource consumption and resource processing.

[0241] For example, at N target location coordinates in the 3D view of the target area, a preset identifier corresponding to the device model is generated, resulting in a 3D view including N alternative camera positions.

[0242] According to embodiments of this disclosure, the dynamic simulation scheme also includes delivery time estimation, which can be displayed as a parameter along with dynamic resource change information on a visualization page of the target terminal device.

[0243] Figure 5 An architectural diagram of a simulation model according to an embodiment of the present disclosure is shown schematically.

[0244] like Figure 5 As shown, the architecture 500 of the simulation model includes an output module 501, a simulation calculation module 502, a configuration module 503, a 3D modeling module 504, an equipment energy consumption module 505, a cabinet energy consumption module 506, and a work order module 507.

[0245] According to embodiments of this disclosure, the output module 501 is used to output the position coordinates of the determined candidate and / or target positions, as well as the dynamic simulation scheme.

[0246] According to embodiments of this disclosure, configuration module 503 is a module for summarizing static information of the data center, and the information sources include computer room, equipment, and maintenance information. The computer room information includes the overall physical space specifications of the computer room, the load-bearing design of each rack, the physical space (in units of U), the network conditions already available inside the racks (whether fiber optic cables and network cables are available and their corresponding quantities), and the rack space already used by each rack.

[0247] Equipment information includes the physical specifications (in units of U) of the equipment as defined during the procurement phase, and the hardware configuration of the equipment.

[0248] Maintenance information includes the SLA status of the data center during the environment preparation phase, such as hardware racking time, network deployment time, system installation time, and the time required to adjust resources if insufficient resources are encountered (e.g., time to add network patch cords or adjust rack power supplies). Hardware racking time, network deployment time, and system installation time are used to determine the environment preparation duration, while the time required to adjust resources if insufficient resources are encountered is the environment adjustment duration.

[0249] According to embodiments of this disclosure, the 3D modeling module 504 includes a scaled-down model of a data center server room, used for simulating and dynamically displaying server room resources and showcasing the 3D model. The 3D modeling module 504 supports layer-by-layer selection and display from data center to server room to module to rack to equipment, realistically reflecting the internal layout of the server room and the usage of its infrastructure.

[0250] The device energy consumption module 505 includes a first power consumption unit and a first heat dissipation unit. The first power consumption unit is used to detect and statistically analyze the power consumption information of multiple device models, and the first heat dissipation unit is used to collect the heat dissipation information of the device in the computer room through a thermal imaging device, and form a heat dissipation model of the device configuration for subsequent calculations.

[0251] The rack power consumption module 506 operates similarly to the equipment power consumption module 505, but its focus is on the rack unit. The rack power consumption module 506 includes a second power consumption unit and a second heat dissipation unit. The second power consumption unit detects and statistically analyzes the power consumption information of multiple racks, while the heat dissipation unit collects heat dissipation information of the rack within the server room using thermal imaging equipment and forms a heat dissipation model for the rack for subsequent calculations.

[0252] The rack power consumption module 506 is also used to obtain power supply specifications. Power supply specifications are fixed during the design phase of the rack and refer to the maximum power supply that the rack can handle. For example, the power consumption of a rack in a medium-density data center is generally 5KW, and the total power consumption of all machines in the rack cannot exceed 5KW.

[0253] The work order module 507 is an information provision unit for devices to be deployed in the data center. Deployment strategies for target devices can be entered into the work order module 507 in the form of work orders. The work order module 507 includes input information such as device model, configuration information, configuration start time, and placement time requirements. During the simulation phase, this information will be used as input for the simulation model's calculations.

[0254] The simulation calculation module 502 comprehensively utilizes static and dynamic information for calculation and simulation.

[0255] Figure 6 An architectural diagram of a simulation computing module according to an embodiment of the present disclosure is shown schematically.

[0256] like Figure 6 As shown, the architecture 600 of the simulation calculation module includes a spatial simulation calculation unit 601, a performance simulation calculation unit 602, and a time-dependent simulation calculation unit 603.

[0257] The spatial simulation calculation unit 601 is used to determine the calculated value of the static spatial index based on the comparison relationship between the first static spatial index value and the second static spatial index value.

[0258] The performance simulation calculation unit 602 is used to determine the calculated value of the static power consumption index based on the comparison relationship between the first static power consumption index value and the second static power consumption index value; and to determine the calculated value of the static heat dissipation index based on the sum of the first static heat dissipation index value and the second static heat dissipation index value.

[0259] The performance simulation calculation unit 602 is also used to determine the calculated value of the dynamic heat dissipation index based on the first static heat dissipation index value and the dynamic heat dissipation index sequence; and to determine the calculated value of the dynamic power consumption index based on the first dynamic power consumption index sequence and the second dynamic power consumption index sequence.

[0260] The time-based simulation calculation unit 603 is used to determine the environmental arrival time based on the equipment model and location coordinates.

[0261] According to embodiments of this disclosure, the space simulation calculation unit 601, the performance simulation calculation unit 602, and the time-dependent simulation calculation unit 603 transmit information to each other, wherein any one of the simulation calculation units can receive information from the other two simulation calculation units and calculate index values ​​or generate dynamic simulation schemes.

[0262] According to another embodiment of this disclosure, the architecture 600 of the simulation calculation module further includes a comprehensive simulation unit, which is used to receive static index calculation values ​​and / or dynamic index calculation values ​​from the space simulation calculation unit 601, the performance simulation calculation unit 602 and the time-sensitivity simulation calculation unit 603, and generate index values ​​and / or dynamic simulation schemes.

[0263] Figure 7 A schematic block diagram of a device deployment apparatus according to an embodiment of the present disclosure is shown.

[0264] like Figure 7 As shown, the device deployment apparatus 700 of this embodiment includes a first determining module 710, a calculation module 720, a second determining module 730, a simulation calculation module 740, and a third determining module 750.

[0265] The first determining module 710 is used to determine the device indicators and configuration information corresponding to the target device according to the deployment strategy of the target device. The device indicators include a first static indicator value and a first dynamic indicator value. In one embodiment, the first determining module 710 can be used to execute the operation S210 described above, which will not be repeated here.

[0266] The calculation module 720 is used to calculate the index value of each idle machine position within the target area based on the first static index value, configuration information, the second static index value corresponding to the target area, and location information. The idle machine positions are used to place the target device. In one embodiment, the calculation module 720 can be used to perform the operation S220 described above, which will not be repeated here.

[0267] The second determining module 730 is used to determine N candidate camera positions within the target area based on the indicator value, where N≥2. In one embodiment, the second determining module 730 can be used to perform the operation S230 described above, which will not be repeated here.

[0268] The simulation calculation module 740 is used to generate N dynamic simulation schemes corresponding to N candidate camera positions based on the first static index value, the first dynamic index value, configuration information, the second dynamic index value corresponding to the target area, and location information. In one embodiment, the simulation calculation module 740 can be used to execute the operation S240 described above, which will not be repeated here.

[0269] The third determining module 750 is used to determine the target machine position from N candidate machine positions based on N dynamic simulation schemes, so as to deploy the target equipment at the target machine position. In one embodiment, the third determining module 750 can be used to perform the operation S250 described above, which will not be repeated here.

[0270] According to embodiments of this disclosure, the first static index value includes a first static space index value, a first static power consumption index value, and a first static heat dissipation index value; the configuration information includes the device model; the second static index value includes a second static space index value, a second static power consumption index value, and a second static heat dissipation index value; and the location information includes location coordinates.

[0271] According to embodiments of this disclosure, the computing module 720 includes a first computing unit, a second computing unit, a third computing unit, a fourth computing unit, and a fifth computing unit.

[0272] The first calculation unit is used to determine the calculated value of the static spatial index based on the comparison relationship between the first static spatial index value and the second static spatial index value.

[0273] The second calculation unit is used to determine the calculated value of the static power consumption index based on the comparison relationship between the first static power consumption index value and the second static power consumption index value.

[0274] The third calculation unit is used to determine the calculated value of the static heat dissipation index based on the sum of the first static heat dissipation index value and the second static heat dissipation index value.

[0275] The fourth calculation unit is used to determine the environmental arrival time based on the equipment model and location coordinates. The environmental arrival time represents the time required to complete the deployment of the target equipment.

[0276] The fifth calculation unit is used to determine the index values ​​based on the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and environmental arrival time.

[0277] According to embodiments of this disclosure, the fourth calculation unit includes a first duration calculation subunit, a second duration calculation subunit, and a third duration calculation subunit.

[0278] The first duration calculation subunit is used to determine the current configuration information and environment preparation time of the idle machine position based on the location coordinates. The environment preparation time represents the basic time required to deploy the equipment.

[0279] The second duration calculation subunit is used to determine the environment adjustment duration based on the current configuration information and equipment model. The environment adjustment duration represents the time required to adjust the environment of the idle machine position to meet the requirements of the equipment model.

[0280] The third duration calculation subunit is used to determine the environmental arrival time based on the environmental preparation time and the environmental adjustment time.

[0281] According to embodiments of this disclosure, the fifth calculation unit includes a first index calculation subunit, a second index calculation subunit, and a third index calculation subunit.

[0282] The first indicator calculation subunit is used to obtain the longest device installation time in the service level agreement. The service level agreement includes multiple device models, and each device model corresponds to multiple device installation times.

[0283] The second indicator calculation subunit is used to calculate the difference between the longest equipment installation time and the longest time for the environment to be in place.

[0284] The third index calculation subunit is used to multiply the calculated values ​​of static space index, static power consumption index, static heat dissipation index, and the difference as the index value.

[0285] According to embodiments of this disclosure, the computing module 720 further includes a sixth computing unit, a seventh computing unit, an eighth computing unit, and a ninth computing unit.

[0286] The sixth calculation unit is used to determine the position adjustment coefficient based on the position coordinates and position configuration strategy.

[0287] The seventh calculation unit is used to determine the quantity adjustment coefficient based on the equipment model and quantity configuration strategy.

[0288] The eighth calculation unit is used to determine the total adjustment coefficient based on the position adjustment coefficient and / or the quantity adjustment coefficient.

[0289] The ninth calculation unit is used to determine the index values ​​based on the total adjustment coefficient, the calculated values ​​of static space index, the calculated values ​​of static power consumption index, the calculated values ​​of static heat dissipation index, and the environmental arrival time.

[0290] According to embodiments of this disclosure, the configuration information further includes a configuration start time, and the dynamic simulation scheme includes dynamic resource change information. The simulation calculation module 740 includes a first simulation calculation unit, a second simulation calculation unit, a third simulation calculation unit, and a fourth simulation calculation unit.

[0291] The first simulation calculation unit is used to obtain the environmental arrival time, which is determined based on the location coordinates and equipment model.

[0292] The second simulation calculation unit is used to determine the ordered time series based on the configuration start time and the time it takes for the environment to arrive.

[0293] The third simulation calculation unit is used to process the first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value using ordered time series, so as to obtain the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence that conform to the ordered time series.

[0294] The fourth simulation calculation unit is used to generate dynamic resource change information based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence.

[0295] According to embodiments of this disclosure, the fourth simulation calculation unit includes a first simulation calculation subunit, a second simulation calculation subunit, and a third simulation calculation subunit.

[0296] The first simulation calculation subunit is used to determine the calculated value of the dynamic power consumption index based on the first dynamic power consumption index sequence and the second dynamic power consumption index sequence.

[0297] The second simulation calculation subunit is used to determine the calculated value of the dynamic heat dissipation index based on the first static heat dissipation index value and the dynamic heat dissipation index sequence.

[0298] The third simulation calculation subunit is used to generate information on dynamic changes in resources based on the calculated values ​​of static space index, dynamic power consumption index, and dynamic heat dissipation index.

[0299] According to an embodiment of this disclosure, the device deployment apparatus 700 further includes a display module for displaying the dynamic simulation scheme on a visualization page of the target terminal device. The visualization page includes a time scale so that users can obtain the dynamic changes of resources at multiple moments by operating the time scale. The time scale is determined based on an ordered time series.

[0300] According to an embodiment of this disclosure, the third determining module 750 includes a camera position determining unit, used to determine a target camera position from the N candidate camera positions based on the resource dynamic change information corresponding to the N candidate camera positions.

[0301] According to embodiments of this disclosure, the dynamic simulation scheme further includes a position view. The simulation calculation module 740 includes a fifth simulation calculation unit. The fifth simulation calculation unit includes a fourth simulation calculation subunit and a fifth simulation calculation subunit.

[0302] The fourth simulation calculation subunit is used to obtain the three-dimensional view of the target area and the target position coordinates of the alternative camera positions.

[0303] The fifth simulation calculation subunit is used to generate a preset identifier corresponding to the device model at the target position coordinates in the three-dimensional view in order to obtain the position view.

[0304] According to embodiments of this disclosure, any plurality of modules among the first determining module 710, the calculation module 720, the second determining module 730, the simulation calculation module 740, and the third determining module 750 may be combined into one module, or any one of these modules may be split into multiple modules. Alternatively, at least some of the functions of one or more of these modules may be combined with at least some of the functions of other modules and implemented in one module.

[0305] According to embodiments of this disclosure, at least one of the first determining module 710, the calculation module 720, the second determining module 730, the simulation calculation module 740, and the third determining module 750 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable method of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three methods. Alternatively, at least one of the first determining module 710, the calculation module 720, the second determining module 730, the simulation calculation module 740, and the third determining module 750 can be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0306] Figure 8 A block diagram of an electronic device suitable for a device deployment method according to an embodiment of the present disclosure is shown schematically.

[0307] like Figure 8 As shown, an electronic device 800 according to an embodiment of this disclosure includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage portion 808 into a random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this disclosure.

[0308] RAM 803 stores various programs and data required for the operation of electronic device 800. Processor 801, ROM 802, and RAM 803 are interconnected via bus 804. Processor 801 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 802 and / or RAM 803. It should be noted that the programs may also be stored in one or more memories other than ROM 802 and RAM 803. Processor 801 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0309] According to embodiments of this disclosure, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to a bus 804. The electronic device 800 may also include one or more of the following components connected to the input / output I / O interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the I / O interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 810 as needed so that computer programs read from it can be installed into the storage section 808 as needed.

[0310] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0311] According to embodiments of this disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to embodiments of this disclosure, the computer-readable storage medium may include ROM 802 and / or RAM 803 and / or one or more memories other than ROM 802 and RAM 803 described above.

[0312] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods shown in the flowchart. When the computer program product is run on a computer system, the program code is used to cause the computer system to implement the methods provided in the embodiments of this disclosure.

[0313] When the computer program is executed by the processor 801, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0314] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 809, and / or installed from a removable medium 811. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0315] In such an embodiment, the computer program can be downloaded and installed from a network via communication section 809, and / or installed from removable medium 811. When the computer program is executed by processor 801, it performs the functions defined in the system of this disclosure embodiment. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0316] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0317] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0318] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure can be combined or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0319] The specific embodiments described above further illustrate the purpose, technical solutions, and beneficial effects of this disclosure. It should be understood that the above descriptions are merely specific embodiments of this disclosure and are not intended to limit this disclosure. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the protection scope of this disclosure.

Claims

1. A method for deploying equipment, comprising: Based on the deployment strategy of the target device, determine the device indicators and configuration information corresponding to the target device, wherein the device indicators include a first static indicator value and a first dynamic indicator value; Based on the first static indicator value, the configuration information, the second static indicator value corresponding to the target area, and the location information, the indicator value of each idle machine space in the target area is calculated, and the idle machine space is used to place the target device; the first static indicator value includes a first static space indicator value, a first static power consumption indicator value, and a first static heat dissipation indicator value; the configuration information includes the device model; the second static indicator value includes a second static space indicator value, a second static power consumption indicator value, and a second static heat dissipation indicator value; and the location information includes location coordinates. Based on the aforementioned index values, N alternative camera positions are determined within the target area, where N ≥ 2; Based on the first static indicator value, the first dynamic indicator value, the configuration information, the second dynamic indicator value corresponding to the target area, and the location information, generate N dynamic simulation schemes corresponding to the N candidate machine positions; as well as Based on the N dynamic simulation schemes, a target location is determined from the N candidate locations so that the target equipment can be deployed at the target location; The step of calculating the indicator value of each available machine position within the target area based on the first static indicator value, the configuration information, the second static indicator value corresponding to the target area, and the location information includes: The calculated value of the static spatial index is determined based on the comparison relationship between the first static spatial index value and the second static spatial index value; The calculated value of the static power consumption index is determined based on the comparison relationship between the first static power consumption index value and the second static power consumption index value. The calculated value of the static heat dissipation index is determined based on the sum of the first static heat dissipation index value and the second static heat dissipation index value. Based on the device model and location coordinates, the environmental arrival time is determined, whereby the environmental arrival time characterizes the time required to complete the deployment of the target device; and The index values ​​are determined based on the calculated values ​​of the static space index, the static power consumption index, the static heat dissipation index, and the environmental arrival time.

2. The method according to claim 1, wherein, The step of determining the environmental arrival time based on the device model and the location coordinates includes: Based on the location coordinates, determine the current configuration information and environment preparation time of the idle machine position, wherein the environment preparation time represents the basic time required to deploy the equipment; Based on the current configuration information and the device model, the environment adjustment duration is determined, whereby the environment adjustment duration represents the time required to adjust the environment of the idle machine slot to meet the requirements of the device model; and The environmental arrival time is determined based on the environmental preparation time and the environmental adjustment time.

3. The method according to claim 1, wherein, The step of determining the index value based on the calculated values ​​of the static space index, the static power consumption index, the static heat dissipation index, and the environmental arrival time includes: Obtain the longest device installation duration in the service level agreement, where the service level agreement includes multiple device models, and each device model corresponds to multiple device installation durations; Calculate the difference between the longest equipment installation time and the environmental arrival time; and The product of the calculated static space index, the calculated static power consumption index, the calculated static heat dissipation index, and the difference is used as the index value.

4. The method according to claim 1, wherein, The step of calculating the indicator value of each available machine position within the target area based on the first static indicator value, the configuration information, the second static indicator value corresponding to the target area, and the location information further includes: Based on the location coordinates and location configuration strategy, determine the location adjustment coefficient; Determine the quantity adjustment coefficient based on the equipment model and quantity configuration strategy; Determine the total adjustment coefficient based on the position adjustment coefficient and / or the quantity adjustment coefficient; and The index value is determined based on the total adjustment coefficient, the calculated value of the static space index, the calculated value of the static power consumption index, the calculated value of the static heat dissipation index, and the environmental arrival time.

5. The method according to claim 1, wherein, The configuration information also includes a configuration start time, and the dynamic simulation scheme includes resource dynamic change information; the first dynamic index value includes a first dynamic power consumption index value, and the second dynamic index value includes a second dynamic power consumption index value and a dynamic heat dissipation index value. The step of generating N dynamic simulation schemes corresponding to the N candidate camera positions based on the first static indicator value, the first dynamic indicator value, the configuration information, the second dynamic indicator value corresponding to the target area, and the location information includes: The environmental arrival time is obtained, and the environmental arrival time is determined based on the location coordinates and the device model; Based on the configuration start time and the arrival time of the environment, an ordered time sequence is determined; The first dynamic power consumption index value, the second dynamic power consumption index value, and the dynamic heat dissipation index value are processed using the ordered time series to obtain a first dynamic power consumption index sequence, a second dynamic power consumption index sequence, and a dynamic heat dissipation index sequence that conform to the ordered time series; and The resource dynamic change information is generated based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence.

6. The method according to claim 5, wherein, Based on the first static heat dissipation index value, the first dynamic power consumption index sequence, the second dynamic power consumption index sequence, and the dynamic heat dissipation index sequence, the resource dynamic change information is generated, including: The calculated value of the dynamic power consumption index is determined based on the first dynamic power consumption index sequence and the second dynamic power consumption index sequence; Based on the first static heat dissipation index value and the dynamic heat dissipation index sequence, the calculated value of the dynamic heat dissipation index is determined; and The resource dynamic change information is generated based on the calculated values ​​of the static space index, the dynamic power consumption index, and the dynamic heat dissipation index.

7. The method according to any one of claims 5-6, further comprising: The dynamic simulation scheme is displayed on the visualization page of the target terminal device. The visualization page includes a time scale, so that users can obtain the dynamic changes of resources at multiple moments by operating the time scale. The time scale is determined based on the ordered time series.

8. The method according to claim 5, wherein, The step of determining the target location from the N candidate locations based on the N dynamic simulation schemes includes: Based on the dynamic resource change information corresponding to the N candidate locations, the target location is determined from the N candidate locations.

9. The method according to claim 5, wherein, The dynamic simulation scheme also includes a position view; The step of generating N dynamic simulation schemes corresponding to the N candidate camera positions based on the first static index value, the first dynamic index value, the configuration information, the second dynamic index value corresponding to the target area, and the location information further includes: Obtain a 3D view of the target area and the target position coordinates of the candidate camera positions; and At the target location coordinates in the three-dimensional view, a preset identifier corresponding to the device model is generated to obtain the location view.

10. An equipment deployment apparatus, comprising: The first determining module is used to determine the device indicators and configuration information corresponding to the target device according to the deployment strategy of the target device. The device indicators include a first static indicator value and a first dynamic indicator value. The calculation module is used to calculate the index value of each idle machine position in the target area based on the first static index value, the configuration information, the second static index value corresponding to the target area, and the location information. The idle machine position is used to place the target device. The first static index value includes a first static space index value, a first static power consumption index value, and a first static heat dissipation index value. The configuration information includes the device model. The second static index value includes a second static space index value, a second static power consumption index value, and a second static heat dissipation index value. The location information includes location coordinates. The second determining module is used to determine N candidate locations within the target area based on the index value, where N≥2; The simulation calculation module is used to generate N dynamic simulation schemes corresponding to the N candidate camera positions based on the first static index value, the first dynamic index value, the configuration information, the second dynamic index value corresponding to the target area, and the location information. as well as The third determining module is used to determine the target machine position from the N candidate machine positions based on the N dynamic simulation schemes, so as to deploy the target equipment at the target machine position; The calculation module is further configured to: determine a static power consumption index calculation value based on the comparison relationship between the first static power consumption index value and the second static power consumption index value; determine a static heat dissipation index calculation value based on the sum of the first static heat dissipation index value and the second static heat dissipation index value; and determine the environmental arrival time based on the device model and the location coordinates, wherein the environmental arrival time characterizes the time required to complete the deployment of the target device. The index value is determined based on the calculated values ​​of the static space index, the static power consumption index, the static heat dissipation index, and the environmental arrival time.

11. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors perform the method according to any one of claims 1 to 9.

12. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 9.

13. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 9.

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