New energy transformer area communication resource management method and device based on entropy value

Abstract

The invention relates to the technical field of electric power communication, in particular to a new energy transformer area communication resource management method and device based on entropy, and the method comprises the steps: virtualizing physical communication resources of a new energy transformer area to obtain virtual resources, and abstracting the virtual resources into services of various businesses; network data of the new energy transformer area are monitored in real time, an entropy value is calculated, and when the entropy value exceeds a set threshold value, service quality optimization is carried out for various services so as to adjust communication resources and reduce the entropy value; wherein the entropy is calculated based on a quality of service metric, the quality of service metric including a response time, a success rate, reliability, and a load rate in the network data. Therefore, the entropy concept is introduced into communication resource management to measure the uncertainty and chaos degree of the system, and by monitoring and controlling the entropy, the orderliness and efficiency of a communication network can be effectively improved, reasonable distribution and utilization of network resources are ensured, and efficient and reliable data transmission of a new energy transformer area is powerfully supported.

Description

Technical Field

[0001] The present application relates to the field of electric power communication technology, and in particular to a method and device for managing communication resources in a new energy station area based on entropy. Background Art

[0002] A new energy station refers to an electricity supply unit that integrates a variety of new energy power generation equipment (such as solar photovoltaic panels, wind turbines, etc.), energy storage systems (such as battery storage) and related power loads (such as residential electricity, industrial and commercial electricity, etc.) within a certain area, and is equipped with advanced communication, control and management technologies to achieve efficient consumption of new energy, balance of electricity supply and demand, and intelligent operation.

[0003] At present, the local communication network of the substation is mainly based on HPLC (high-speed power line carrier communication) and wireless private network. With the digital construction of new energy substations, the frequency of business collection such as minute-level collection of electricity information, distributed photovoltaic regulation, box-type energy storage monitoring and low-voltage distribution monitoring is high, and the business scale has grown explosively. In actual applications, due to the lack of communication resource management, the existing local communication network faces serious conflicts in wired / wireless channel resources in the face of high-frequency collection needs, and cannot provide a reliable and stable communication network to support the construction of "observable, measurable, adjustable and controllable" new energy substations. Summary of the invention

[0004] In order to overcome the deficiencies in the prior art, the present application provides a new energy station area communication resource management method and device based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the rational allocation and utilization of network resources.

[0005] In a first aspect, the present application provides a method for managing communication resources in a new energy station area based on entropy value, the method comprising the following steps:

[0006] Virtualizing the physical communication resources of the new energy station area to obtain virtual resources, and abstracting the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services;

[0007] Monitor the network data of the new energy station area in real time and calculate the entropy value. When the entropy value exceeds the set threshold, optimize the service quality for various types of services to adjust communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes response time, success rate, reliability and load rate in the network data.

[0008] In a possible implementation, the physical communication resources of the new energy station area are virtualized to obtain virtual resources using software defined network SDN and network function virtualization NFV.

[0009] In a possible implementation, the entropy value H′ is calculated by the following formula: i (p):

[0010] H′ i (p) = -lnH i (p)

[0011]

[0012] Among them, H i (p) represents the QoS scale of communication resources; Q ij represents the quality of service of the i-th available channel selected for the j-th service communication, and Q ij =(Q ijk ,1≤k≤4), k represents the number of the service quality metric, max(Q ijk ) indicates Q ij The maximum value of the kth quality of service metric, w represents the weight of the quality of service metric, w = (w k ,1≤k≤4,Σw k =1).

[0013] In a possible implementation, for control services / collection services, a local search algorithm is used to optimize the service quality, including the following steps:

[0014] Determine the number of control service / collection service requests, and for each control service / collection service request, determine the number of communication resources that meet the conditions;

[0015] Randomly select one from each communication resource requested by the control service / collection service to form an initial resource allocation scheme as the initial solution, and set an objective function that minimizes the entropy value and meets the upper limit requirement of the service response time;

[0016] A random perturbation strategy is used to obtain the initial point, and the domain structure is defined based on the response time critical path node sequence to determine the communication resource adjustment direction;

[0017] Starting from the initial solution, search within the defined neighborhood structure, adjust the current resource allocation scheme, and obtain the neighborhood solution;

[0018] Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether it meets the objective function requirements; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure; until the set stop condition is met, output the current optimal solution as the optimized resource allocation plan.

[0019] In one possible implementation, the random perturbation strategy is formulated as follows:

[0020] During the search within the defined neighborhood structure, record the number of consecutive steps without finding a better solution, and record the degree of convergence for the consecutive set number of steps;

[0021] If the number of consecutive steps without searching for a better solution reaches the set first threshold, or the degree of convergence of the set number of consecutive steps is less than the set second threshold, the current neighborhood solution is randomly perturbed.

[0022] In one possible implementation, the domain structure is defined by the following formula:

[0023]

[0024] Among them, x i ∈X k , X k =(x1,x2...x n ) is the X response time critical path node sequence.

[0025] In a possible implementation manner, when optimizing the quality of service for maintenance services, the following steps are included:

[0026] When it is detected that the data packet loss rate exceeds a third threshold, the transmission rate is reduced and the channel time slot is reduced;

[0027] When it is detected that the traffic transmission volume increases and the load rate does not exceed the fourth threshold, the transmission rate is increased and the channel time slot is increased; when it is detected that the traffic transmission volume increases and the load rate exceeds the fourth threshold, a new channel is enabled according to the priority;

[0028] When it is detected that the channel utilization rate is lower than the fifth threshold, channel recovery is performed; when it is detected that the channel utilization rate is higher than the sixth threshold, a new channel is enabled according to the priority.

[0029] In a second aspect, the present application provides a new energy station area communication resource management device based on entropy value, the device comprising:

[0030] A conversion module, used to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services;

[0031] The management module is used to monitor the network data of the new energy station area in real time and calculate the entropy value. When the entropy value exceeds the set threshold, the service quality is optimized for various types of services to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0032] In the third aspect, the present application provides an electronic device comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the new energy station area communication resource management method based on entropy value as described in any one of the first aspects are performed.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the entropy-based new energy station area communication resource management method as described in any one of the first aspects are executed.

[0034] This embodiment provides a method and device for managing communication resources in a new energy station area based on entropy value, which virtualizes the physical communication resources in the new energy station area to obtain virtual resources, and abstracts the virtual resources into services for various types of businesses; monitors the network data of the new energy station area in real time and calculates the entropy value, and when the entropy value exceeds the set threshold, optimizes the service quality for various types of businesses to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data. Thus, the concept of entropy value is introduced into communication resource management to measure the uncertainty and chaos of the system, and by monitoring and controlling the entropy value, the orderliness and efficiency of the communication network can be effectively improved, the reasonable allocation and utilization of network resources can be ensured, and the efficient and reliable transmission of data in the new energy station area can be strongly supported. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A flowchart of a method for managing new energy area communication resources based on entropy value according to an embodiment of the present application is shown;

[0037] Figure 2 A flow chart showing the optimization of service quality for control services / collection services according to an embodiment of the present application is shown;

[0038] Figure 3 A schematic diagram of the structure of a new energy area communication resource management device based on entropy value according to an embodiment of the present application is shown;

[0039] Figure 4A structural block diagram of an electronic device described in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0040] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of order, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0041] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0042] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0043] In view of the technical problems raised by the background technology, the present application provides a new energy station area communication resource management method and device based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the rational allocation and utilization of network resources.

[0044] In one embodiment, see the attached specification Figure 1 The present application provides a method for managing communication resources in a new energy area based on entropy value, the method comprising the following steps:

[0045] S1. Virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services;

[0046] S2. Monitor the network data of the new energy station area in real time and calculate the entropy value. When the entropy value exceeds the set threshold, optimize the service quality for each type of business to adjust the communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0047] In step S1, the physical communication resources of the new energy station area can be virtualized to obtain virtual resources using software defined network SDN and network function virtualization NFV, and the virtual resources can be abstracted into services for various businesses for flexible adjustment and efficient utilization.

[0048] For example, by deploying an SDN controller and connecting it to physical network devices (such as switches, routers, etc.) in the new energy area, the controller can be used to centrally manage and control network devices by configuring the communication protocol between the controller and the device. The SDN controller collects resource information of physical network devices, including the number of ports, port rate, link bandwidth, device load, etc., and then abstracts the physical network resources into virtual resources based on this information. The SDN controller can then dynamically combine and configure the resources of physical network devices according to the needs of upper-layer services to form a virtual network topology and provide customized network services for different services.

[0049] Alternatively, build an NFV management platform, install virtualization software on a general-purpose server to create a virtual machine or container environment, and deploy network functions (such as firewalls, load balancing, intrusion detection, etc.) in these virtual machines or containers in the form of software. The NFV management platform divides the server's physical resources (CPU, memory, storage, etc.) into multiple virtual resource pools based on business needs, and allocates them to different virtual network functions. The NFV management platform then decouples network functions from dedicated hardware devices and runs them on general-purpose servers in the form of software. These software-based network functions can be flexibly deployed and configured according to demand and become part of the service.

[0050] In addition, it is necessary to conduct a detailed analysis of the communication needs within the new energy area, clarify which services require high-frequency collection, which services require real-time monitoring, and the specific requirements of these services for communication resources. In this application, the business types in the new energy area are divided into control, collection and maintenance, and multiple dedicated channels are equipped for each type of business. Among them, control services have the highest priority in the new energy area. These services have extremely high real-time requirements, and it is necessary to ensure that control instructions can reach the execution equipment in a timely and accurate manner; collection services are mainly responsible for collecting data from various equipment and environments in the new energy area. The dedicated channels of these services need to have a high bandwidth and a certain reliability to ensure that a large amount of real-time data can be quickly and accurately transmitted to the data center for analysis and processing; maintenance services are mainly used to handle faults and problems in the communication system, and their dedicated channels need to have rapid response capabilities and a certain priority, so that fault information and maintenance instructions can be transmitted in time when a fault occurs.

[0051] In step S2, the uncertainty and confusion in the communication network of the new energy area are judged by calculating the entropy value, and the multi-mode mutual communication technology capability of the active distribution network is improved based on this, and the communication resource management is continuously optimized, thereby improving the orderliness and efficiency of the communication network. Among them, when the entropy value is monitored to increase, it indicates that the uncertainty and confusion in the system increase. In order to timely adjust and optimize the allocation of communication resources and ensure the efficiency and reliability of control services, the entropy value needs to be reduced in time.

[0052] Specifically, in this application, response time, success rate, reliability and load rate are used as service quality QoS metrics, and they are quantitatively defined respectively.

[0053] The response time consists of three parts: local processing time T deal (R ij ), system intermediate overhead T mid (R ij ) and network transmission time T net (R ij ), the total response time is Q ij.time =T deal (R ij )+T mid (R ij )+T net (R ij ).

[0054] The success rate is the ratio of the number of successful business transmissions to the total number of transmissions: Where N r (R ij ) indicates that the service is in channel R ij Number of successful transmissions, N f (Rij ) indicates that the service is in channel R ij The number of failed transfers.

[0055] The reliability is the probability that the channel is available Where T r (R ij ) represents the channel resource R ij The average available time, T f (R ij ) indicates resource R ij The average unavailable time.

[0056] The load rate is the traffic in channel R ij Load rate Where T u (R ij ) indicates the occupied resources, T n (R ij ) indicates unused resources.

[0057] Then let R ij It means that the i-th available channel is selected after searching for the realization of the j-th service, and the resource R ij The quality of service is denoted as Q ij , represented by the following vector: Q ij =(Q ij.time ,Q ij.suc_rate ,Q ij.reliability ,Q ij.load ). We also define entropy in:

[0058]

[0059]

[0060] Where w=(w k ,1≤k≤4,Σw k =1) represents the weight of the service quality metric; in this application, Q ij.time is a negative measure, the higher the value, the lower the quality; positive measures include Q ij.suc_rate , Q ij.reliability , Q ij.load The higher the value, the higher the quality. The constructed entropy function H i (p) can characterize the QoS scale of communication resources. According to this definition, the more stable the QoS of communication resources is, the greater the cost-effectiveness of the resources is. i (p) is larger, then H′ i (p) = -lnH i (p), that is, by taking the negative logarithm, we get the QoS stability scale - entropy scale that characterizes the communication resources.

[0061] See the instruction manual Figure 2 When optimizing the service quality for control services / collection services, a local search algorithm is used, including the following steps:

[0062] S201, determining the number of control service / collection service requests, and for each control service / collection service request, determining the number of communication resources that meet the conditions;

[0063] S202, randomly select one from each communication resource requested by the control service / collection service to form an initial resource allocation scheme as an initial solution, and set an objective function that minimizes the entropy value and meets the upper limit requirement of the service response time;

[0064] S203, using a random perturbation strategy to obtain an initial point, and defining a domain structure based on a response time critical path node sequence to determine a communication resource adjustment direction;

[0065] S204, starting from the initial solution, searching in the defined neighborhood structure, adjusting the current resource allocation scheme, and obtaining a neighborhood solution;

[0066] S205. Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether the objective function requirement is met; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure; until the set stop condition is met, output the current optimal solution as the optimized resource allocation plan.

[0067] In step S201, the number of control service / collection service requests in the system is determined, and for each control service / collection service request, the number of communication resources that meet the conditions is determined. These communication resources cover different attributes such as channels, bandwidths, and transmission rates, forming a resource set for selection. For example, there are M1 control service requests in the system, and each service request has N1 communication resources that can meet the conditions. Find a solution from the solutions to optimize in order to reduce the entropy value; for example, there are M2 collection service requests in the system, and each service request has N2 communication resources that can meet the conditions. Find a solution to optimize among the solutions to reduce the entropy value.

[0068] In step S202, one communication resource is randomly selected from multiple communication resources requested by each control service / collection service to form an initial resource allocation scheme as an initial solution. For example, for the control service of distributed power generation device A, wireless communication channel 1 is randomly selected; for device B, wired Ethernet link 2 is selected, etc. At the same time, an objective function is set to minimize the entropy value and meet the upper limit requirement of the service response time, which is related to the response time, success rate, reliability and load rate, and is calculated by the above formula.

[0069] In step S203, in order to avoid the initial solution falling into the local optimum, a random perturbation strategy is used to obtain the initial point; and the algorithm domain structure is defined according to the response time key path node sequence to clarify the resource adjustment direction. In one embodiment, the domain structure is defined by the following formula:

[0070]

[0071] Among them, x i ∈X k , X k =(x1,x2...x n ) is a sequence of critical path nodes for response time X. The critical path node sequence for response time includes nodes that have the greatest impact on response time in the entire process from the issuance of a business instruction to its final execution, such as a control instruction issuance node, a network transmission node, a device receiving node, etc.

[0072] In step S204-step S205, during the search process within the defined neighborhood structure starting from the initial solution, the number of consecutive steps in which a better solution is not found is recorded, as well as the degree of convergence of the consecutive set number of steps. If the number of consecutive steps in which a better solution is not found reaches a set first threshold, or the degree of convergence of the consecutive set number of steps is less than a set second threshold, the current neighborhood solution is randomly perturbed.

[0073] Specifically, during the search process within the defined neighborhood structure, after each certain number of steps of neighborhood search, it is determined whether it has fallen into a local minimum state. The basis for the determination is whether a better solution of the objective function, that is, a solution with a smaller entropy value and a better response time, has not been found in consecutive steps. For example, in the process of optimizing control-type business resources, if after adjusting the resource allocation plan for 10 consecutive steps, the resource QoS entropy has not decreased or the service response time has not been further improved, then it is very likely that the current solution is already a local minimum solution, and continuing to search in this direction may not yield a global optimal solution. In this case, a random perturbation strategy is executed to jump out of the local minimum area and continue searching;

[0074] Alternatively, during the search within the defined neighborhood structure, if the convergence degree is too small within a certain number of consecutive steps, it means that the solution changes very little, which indicates that the algorithm has approached a stable state, but this state may only be a local optimum rather than a global optimum. For example, when optimizing resources for collection services, if the adjustment of resource allocation for 100 consecutive steps only brings about a slight change in resource QoS entropy, it is necessary to execute a random perturbation strategy and re-search the search direction to jump out of the local minimum.

[0075] When the stopping condition is met (such as no better solution is found in consecutive steps), the search is stopped and the current optimal solution is output. The optimal solution is the resource allocation plan optimized for control services / collection services, which can minimize resource entropy while meeting the upper limit requirements of service response time, thereby ensuring the efficiency and reliability of control services / collection services.

[0076] In addition, for maintenance services, a higher packet loss rate will increase the stability entropy of the system. A high load rate may lead to unbalanced resource allocation and increased data transmission delay, thereby increasing the uncertainty of the system and increasing the entropy value. For maintenance services, too high or too low channel utilization is not conducive to the stable operation of the system, which in turn affects the entropy value. When optimizing the quality of service: when it is detected that the packet loss rate exceeds the third threshold, the transmission rate is reduced and the channel time slot is reduced; when it is detected that the service transmission volume increases and the load rate does not exceed the fourth threshold, the transmission rate is increased and the channel time slot is increased; when it is detected that the service transmission volume increases and the load rate exceeds the fourth threshold, a new channel is enabled according to the priority; when it is detected that the channel utilization rate is lower than the fifth threshold, the channel is recycled; when it is detected that the channel utilization rate is higher than the sixth threshold, a new channel is enabled according to the priority.

[0077] Specifically, when a high packet loss rate is detected, measures are first taken to reduce the transmission rate and channel time slots. This step aims to initially alleviate the problem of packet loss by reducing the amount of data transmission and the channel occupancy rate. It may be because the current channel load capacity cannot withstand the current transmission rate or the time slot setting is unreasonable, resulting in packet loss. Further, if the problem persists, feedback is immediately given to the platform and the staff is notified for maintenance. At the same time, the transmission of the channel service is interrupted, and the service request is sorted in the storage area according to priority. For control services, additionally notify the staff to add a new channel for transmission to ensure the continuity of the control instructions and avoid affecting the control function of the system due to channel failure. If it is determined that the channel is interfered but the interference is not continuous, the transmission of the channel service is interrupted, and the transmission is resumed after the interference ends, reducing the impact of unstable interference on service data. If the interference persists, feedback is also given to the platform and the staff is notified for maintenance, and the transmission of the channel service is interrupted, waiting in the storage area. For control services, a new channel is notified to ensure the normal operation of the service during the channel repair period.

[0078] When an increase in business transmission volume is detected, first determine whether the load rate of the occupied channel exceeds 80%. The setting of this threshold is based on the channel's load carrying capacity and performance optimization considerations. Exceeding this load rate may cause transmission delays, packet loss and other problems. Among them, if the load rate does not exceed 80%, the transmission rate is accelerated and the channel time slot is increased to make full use of the existing channel resources to meet the increased business transmission needs. If the demand still cannot be met, further determine whether there are idle channels so that resources can be expanded when necessary. If the load rate exceeds 80% and there are idle channels, new channels are enabled to share the business transmission pressure. If the existing resources are insufficient, for control services, immediately notify the staff to add additional new channels to ensure the normal operation of their high-priority services; for collection services that interrupt low-priority requests, higher-priority requests are assigned to the vacated channels, and limited resources are reasonably allocated to prioritize the data transmission of important services.

[0079] When it is detected that the channel utilization rate is lower than 10%, it is further determined whether the occupied channel has sufficient capacity. If there is not enough capacity, it will not be recycled to avoid insufficient resources for subsequent business transmission due to the recycling of channels; if there is enough capacity, the business will be migrated to the channel with lower utilization rate, and re-sorted according to the priority of the business request, and the channel with low utilization rate will be recycled to improve the overall utilization rate of channel resources. When the channel utilization rate is higher than 80%, it is first determined whether there is an idle channel. If so, a new channel is enabled; if not, for control services, the staff is immediately notified to add a new channel, and for collection services, low-priority requests are interrupted, and higher-priority requests are allocated to the vacated channel to ensure that channel resources can meet business needs and avoid affecting business performance due to channel overload.

[0080] It can be seen that the entropy-based communication resource management method for new energy stations provided in this application can effectively measure and control the uncertainty and chaos in the communication network by introducing the concept of entropy, thereby improving the orderliness and efficiency of the communication network. It can also flexibly respond to various communication needs, especially in the dual-service scenarios of high-frequency collection and real-time monitoring in new energy stations, ensuring the stability and reliability of the communication network.

[0081] Based on the same inventive concept, an entropy-based new energy substation communication resource management device is also provided in an embodiment of the present application. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned entropy-based new energy substation communication resource management method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0082] As the instruction manual Figure 3 As shown, an embodiment of the present application provides a new energy area communication resource management device based on entropy value, the device comprising:

[0083] The conversion module 301 is used to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services;

[0084] The management module 302 is used to monitor the network data of the new energy station area in real time and calculate the entropy value, and when the entropy value exceeds the set threshold, optimize the service quality for various types of services to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

[0085] In one embodiment, the conversion module 301 virtualizes the physical communication resources of the new energy station area to obtain virtual resources using software defined network SDN and network function virtualization NFV.

[0086] In one embodiment, the management module 302 calculates the entropy value H′ by the following formula: i (p):

[0087] H′ i (p) = -lnH i (p)

[0088]

[0089] Among them, H i (p) represents the QoS scale of communication resources; Q ij represents the quality of service of the i-th available channel selected for the j-th service communication, and Q ij =(Q ijk ,1≤k≤4), k represents the number of the service quality metric, max(Q ijk ) indicates Q ij The maximum value of the kth quality of service metric, w represents the weight of the quality of service metric, w = (w k ,1≤k≤4,Σw k =1).

[0090] In one embodiment, the management module 302 uses a local search algorithm to optimize the service quality for control services / collection services, including: determining the number of requests for control services / collection services, and for each control service / collection service request, determining the number of communication resources that meet the conditions; randomly selecting one from the communication resources of each control service / collection service request to form an initial resource allocation scheme as an initial solution, and setting an objective function that minimizes the entropy value and meets the upper limit requirements of the service response time; using a random perturbation strategy to obtain an initial point, and defining a domain structure based on a response time critical path node sequence to determine the direction of communication resource adjustment; starting from the initial solution, searching in a defined neighborhood structure, adjusting the current resource allocation scheme, and obtaining a neighborhood solution; calculating the entropy value and service response time corresponding to each neighborhood solution to determine whether the objective function requirements are met; if so, updating the current optimal solution to the neighborhood solution; if not, continuing to search in the defined neighborhood structure; until the set stop condition is met, outputting the current optimal solution as the optimized resource allocation scheme.

[0091] In one embodiment, the management module 302 formulates a random perturbation strategy in the following manner: during the search within the defined neighborhood structure, the number of consecutive steps in which a better solution is not found, and the degree of convergence of the consecutive set number of steps are recorded; if the number of consecutive steps in which a better solution is not found reaches a set first threshold, or the degree of convergence of the consecutive set number of steps is less than a set second threshold, the current neighborhood solution is randomly perturbed.

[0092] In one embodiment, the management module 302 defines the domain structure by the following formula:

[0093]

[0094] Among them, x i ∈X k , X k =(x1,x2...x n ) is the X response time critical path node sequence.

[0095] In one embodiment, when the management module 302 optimizes the service quality for maintenance services, it includes: when it is detected that the data packet loss rate exceeds the third threshold, reducing the transmission rate and reducing the channel time slot; when it is detected that the service transmission volume increases and the load rate does not exceed the fourth threshold, increasing the transmission rate and increasing the channel time slot; when it is detected that the service transmission volume increases and the load rate exceeds the fourth threshold, enabling a new channel according to the priority; when it is detected that the channel utilization rate is lower than the fifth threshold, performing channel recovery; when it is detected that the channel utilization rate is higher than the sixth threshold, enabling a new channel according to the priority.

[0096] The present application provides a communication resource management device for a new energy station area based on entropy value, which virtualizes the physical communication resources of the new energy station area to obtain virtual resources through a conversion module, and abstracts the virtual resources into services for various types of businesses; monitors the network data of the new energy station area in real time and calculates the entropy value through a management module, and when the entropy value exceeds the set threshold, optimizes the service quality for various types of businesses to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data. Thus, the concept of entropy value is introduced into communication resource management to measure the uncertainty and chaos of the system, and by monitoring and controlling the entropy value, the orderliness and efficiency of the communication network can be effectively improved, the reasonable allocation and utilization of network resources can be ensured, and the efficient and reliable transmission of data in the new energy station area can be strongly supported.

[0097] Based on the same concept of the present invention, the specification is attached Figure 4 As shown, the structure of an electronic device 400 provided in an embodiment of the present application includes: at least one processor 401, at least one network interface 404 or other user interface 403, a memory 405, and at least one communication bus 402. The communication bus 402 is used to realize the connection and communication between these components. The electronic device 400 optionally includes a user interface 403, including a display (for example, a touch screen, LCD, CRT, holographic imaging (Holographic) or projection (Projector), etc.), a keyboard or a pointing device (for example, a mouse, a trackball (trackball), a touch pad or a touch screen, etc.).

[0098] The memory 405 may include a read-only memory and a random access memory, and provides instructions and data to the processor 401. A portion of the memory 405 may also include a non-volatile random access memory (NVRAM).

[0099] In some implementations, the memory 405 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof:

[0100] Operating system 4051, including various system programs for implementing various basic services and processing hardware-based tasks;

[0101] The application module 4052 includes various application programs, such as a launcher, a media player, a browser, etc., which are used to implement various application services.

[0102] In an embodiment of the present application, by calling the program or instructions stored in the memory 405, the processor 401 is used to execute steps in a new energy station area communication resource management method based on entropy value, which can effectively improve the orderliness and efficiency of the communication network through entropy value monitoring and management, and ensure the rational allocation and utilization of network resources.

[0103] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the method for managing communication resources in a new energy station area based on entropy are executed.

[0104] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, the above-mentioned entropy-based new energy station area communication resource management method can be executed.

[0105] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0106] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0108] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0109] Finally, it should be noted that the above embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the aforementioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for managing communication resources in new energy areas based on entropy, characterized in that: The method comprises the following steps: Virtualizing the physical communication resources of the new energy station area to obtain virtual resources, and abstracting the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services; Monitor the network data of the new energy station area in real time and calculate the entropy value. When the entropy value exceeds the set threshold, optimize the service quality for various types of services to adjust communication resources to reduce the entropy value. The entropy value is calculated based on the service quality metric, and the service quality metric includes response time, success rate, reliability and load rate in the network data.

2. According to claim 1, a method for managing new energy area communication resources based on entropy value, characterized in that: in, Software-defined networking (SDN) and network function virtualization (NFV) are used to virtualize the physical communication resources of the new energy station area to obtain virtual resources.

3. According to the entropy-based new energy area communication resource management method of claim 1, it is characterized in that: The entropy value H' is calculated by the following formula i (p): H′ i (p)=-lnH i (p) Among them, H i (p) represents the QoS scale of communication resources; Q ij represents the quality of service of the i-th available channel selected for the j-th service communication, and Q ij =(Q ijk ,1≤k≤4), k represents the number of the service quality metric, max(Q ijk ) indicates Q ij The maximum value of the kth quality of service metric, w represents the weight of the quality of service metric, w = (w k ,1≤k≤4,Σw k =1).

4. According to claim 3, a method for managing new energy area communication resources based on entropy value, characterized in that: For control services / collection services, a local search algorithm is used to optimize the service quality, including the following steps: Determine the number of control service / collection service requests, and for each control service / collection service request, determine the number of communication resources that meet the conditions; Randomly select one from each communication resource requested by the control service / collection service to form an initial resource allocation scheme as the initial solution, and set an objective function that minimizes the entropy value and meets the upper limit requirement of the service response time; A random perturbation strategy is used to obtain the initial point, and the domain structure is defined based on the response time critical path node sequence to determine the communication resource adjustment direction; Starting from the initial solution, search within the defined neighborhood structure, adjust the current resource allocation scheme, and obtain the neighborhood solution; Calculate the entropy value and service response time corresponding to each neighborhood solution to determine whether it meets the objective function requirements; if so, update the current optimal solution to the neighborhood solution; if not, continue searching within the defined neighborhood structure; until the set stop condition is met, output the current optimal solution as the optimized resource allocation plan.

5. According to claim 4, a method for managing new energy area communication resources based on entropy value, characterized in that: in, The random perturbation strategy is formulated as follows: During the search within the defined neighborhood structure, record the number of consecutive steps without finding a better solution, and record the degree of convergence for the consecutive set number of steps; If the number of consecutive steps without searching for a better solution reaches the set first threshold, or the degree of convergence of the set number of consecutive steps is less than the set second threshold, the current neighborhood solution is randomly perturbed.

6. According to claim 4, a method for managing new energy area communication resources based on entropy value, characterized in that: The domain structure is defined by the following formula: Among them, x i ∈Xk,Xk=(x1,x2...x n ) is the X response time critical path node sequence.

7. According to claim 4, a method for managing new energy area communication resources based on entropy value, characterized in that: When optimizing the service quality for maintenance services, the following steps are included: When it is detected that the data packet loss rate exceeds a third threshold, the transmission rate is reduced and the channel time slot is reduced; When it is detected that the traffic transmission volume increases and the load rate does not exceed the fourth threshold, the transmission rate is increased and the channel time slot is increased; when it is detected that the traffic transmission volume increases and the load rate exceeds the fourth threshold, a new channel is enabled according to the priority; When it is detected that the channel utilization rate is lower than the fifth threshold, channel recovery is performed; when it is detected that the channel utilization rate is higher than the sixth threshold, a new channel is enabled according to the priority.

8. A new energy area communication resource management device based on entropy value, characterized in that: The device comprises: A conversion module, used to virtualize the physical communication resources of the new energy station area to obtain virtual resources, and abstract the virtual resources into services of various types of services; the various types of services include at least one of control services, collection services, and maintenance services; The management module is used to monitor the network data of the new energy station area in real time and calculate the entropy value. When the entropy value exceeds the set threshold, the service quality is optimized for various types of services to adjust the communication resources to reduce the entropy value; wherein the entropy value is calculated based on the service quality metric, and the service quality metric includes the response time, success rate, reliability and load rate in the network data.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via the bus. When the machine-readable instructions are executed by the processor, the steps of the new energy station area communication resource management method based on entropy value are performed as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of the method for managing new energy station area communication resources based on entropy as described in any one of claims 1 to 7.

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