A task offloading node selection method and system

Abstract

The present invention discloses a task offloading node selection method and system, including: obtaining terminal services, judging whether the terminal services are initiated for the first time; if it is initiated for the first time, selecting the optimal multi-access edge computing node according to the latency, multi-access edge computing node load and service processing efficiency, and making a node identifier for the multi-access edge computing node, storing the node identifier of the multi-access edge computing node; if it is not initiated for the first time, unloading the terminal services to the corresponding multi-access edge computing node for processing according to the stored node identifier. Through the node identifier of the multi-access edge computing node, when the service is not initiated for the first time, the service is directly unloaded to the multi-access edge computing node corresponding to the node identifier for execution, without executing the multi-access edge computing node selection algorithm, saving computing resources and effectively reducing system latency.

Description

Technical Field

[0001] The present invention relates to the field of mobile communication technology, and in particular to a task offloading node selection method and system. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] As application requirements increase, the gap between the limited capabilities of the terminal and application requirements becomes larger and larger. Multi-access edge computing (MEC) is an effective technology to solve the above problems. In the MEC system, MEC nodes with certain computing resources and communication resources are set at the edge of the network close to the user. When a user initiates a service, the optimal MEC is selected through some algorithms or strategies (for example: lowest service latency, lowest energy consumption, etc.). The user offloads the service (or task) to this MEC node for processing, greatly reducing the service processing latency or energy consumption. However, the inventors found that there are at least the following problems in the prior art: each time a user initiates a service and offloads a task, the MEC node selection algorithm must be executed first, which consumes the computing resources of the terminal or network node and increases the task latency. Summary of the invention

[0004] In order to solve the above problems, the present invention proposes a task offloading node selection method and system. Through the node identification of the multi-access edge computing node, when the service is not initiated for the first time, the service is directly offloaded to the multi-access edge computing node corresponding to the node identification for execution, without executing the multi-access edge computing node selection algorithm, saving computing resources and effectively reducing system latency.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a task offloading node selection method, comprising:

[0007] Obtain terminal services and determine whether the terminal services are initiated for the first time;

[0008] If it is the first time to initiate, the optimal multi-access edge computing node is selected according to the latency, multi-access edge computing node load and business processing efficiency, and a node identifier is generated for the multi-access edge computing node, and the node identifier of the multi-access edge computing node is stored;

[0009] If it is not the first time to initiate, the terminal service is offloaded to the corresponding multi-access edge computing node for processing according to the stored node identifier.

[0010] As an optional implementation, the node identifier has a total of 32 bits, which respectively represent reserved bits, multi-access edge computing node status, multi-access edge computing node type, different MEC sharing areas, different multi-access edge computing nodes in the MEC sharing area, and different users under the multi-access edge computing node.

[0011] As an optional implementation, the state of the multi-access edge computing node includes an abnormal unloading state and a normal service state, which are represented by 0 and 1 respectively.

[0012] As an optional implementation, the multi-access edge computing node type includes a general multi-access edge computing node and a dedicated multi-access edge computing node, which are represented by 0 and 1 respectively.

[0013] As an optional implementation, the node identifier has a total of 32 bits, of which bits 1-2 are reserved, bit 3 indicates the multi-access edge computing node status, bit 4 indicates the multi-access edge computing node type; bits 5-7 indicate different MEC shared areas; bits 8-12 indicate different multi-access edge computing nodes within the MEC shared area, and bits 13-32 indicate different users under the multi-access edge computing node.

[0014] As an optional implementation method, the task offloading node selection method also includes: if the terminal service is not initiated for the first time, determining the corresponding target multi-access edge computing node according to the stored node identifier, and judging whether the target multi-access edge computing node meets the service requirements. If not, triggering the reselection of the multi-access edge computing node, and unloading the terminal service to the reselected multi-access edge computing node for processing, and at the same time, saving the node identifier of the reselected multi-access edge computing node.

[0015] As an optional implementation, the delay includes the uplink and downlink transmission delay of task offloading, the multi-access edge computing node computing task delay and the task migration delay of terminal movement;

[0016] The business processing benefits include the operator's business service charges and costs;

[0017] The cost includes the computing cost of multiple access edge computing nodes and the network transmission cost.

[0018] In a second aspect, the present invention provides a task offloading node selection system, comprising:

[0019] The receiving module is configured to obtain the terminal service and determine whether the terminal service is initiated for the first time;

[0020] The initial service node selection module is configured to select the optimal multi-access edge computing node according to the latency, the multi-access edge computing node load and the service processing efficiency if the service is initiated for the first time, and to generate a node identifier for the multi-access edge computing node and store the node identifier of the multi-access edge computing node;

[0021] The non-initial service node selection module is configured to offload the terminal service to the corresponding multi-access edge computing node for processing according to the stored node identifier if it is not the first time to initiate the service.

[0022] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in the first aspect is performed.

[0023] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions, wherein when the computer instructions are executed by a processor, the method described in the first aspect is performed.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The present invention provides a task offloading node selection method. When a user initiates a service for the first time, the optimal MEC node is selected according to latency, MEC node load, and efficiency, and its own MEC identifier is sent to the user; when the user initiates the service again, the task is directly offloaded to the target MEC for processing according to the saved MEC identifier, thereby saving computing resources and eliminating the need to execute a node selection algorithm each time to select a service MEC node.

[0026] The present invention assists user task offloading through MEC identification. Each MEC node is assigned an MEC identification. When the user initiates a service again, the task is directly offloaded to the MEC corresponding to the MEC identification for processing, thereby reducing latency.

[0027] The present invention judges the target MEC. When the target MEC does not meet the business requirements, the reselection of the MEC node is triggered, and the task is unloaded to the reselected MEC node for processing. After the task processing is completed, the reselected MEC also sends its own MEC identifier to the user. That is, the node selection algorithm is executed only when the stored target MEC node does not meet the business requirements. From the perspective of the entire system, the latency can be effectively reduced.

[0028] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0030] Figure 1 A schematic diagram of the MEC node network provided in Example 1 of the present invention;

[0031] Figure 2 A flowchart of selecting a task offloading node when a user initiates a service for the first time provided by Embodiment 1 of the present invention;

[0032] Figure 3 A schematic diagram of node identification of a multi-access edge computing node provided in Embodiment 1 of the present invention;

[0033] Figure 4 This is a flowchart of selecting a task offloading node when a user does not initiate a service for the first time provided by Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0034] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0035] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0036] It should be noted that the terms used herein are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that the terms "include" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0037] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0038] Example 1

[0039] like Figure 1As shown, the MEC system constructed in this embodiment consists of a two-layer architecture; the bottom layer is the access point, which is responsible for accessing the UE, for example: the base station of the existing network; the upper layer is the multi-access edge computing node, that is, the MEC node, and multiple MEC nodes form a MEC shared area, which is responsible for processing UE offloading tasks; the access point is fully interconnected with each MEC node in the MEC shared area, and the MEC nodes are fully interconnected.

[0040] Based on the above-mentioned MEC node networking structure, when a user initiates a service for the first time, this embodiment proposes a multi-access edge computing node selection method for task offloading, such as Figure 2 As shown, the specific steps include:

[0041] (1) obtaining a terminal service, where the terminal service is initiated for the first time;

[0042] (2) Select the optimal multi-access edge computing node based on latency, multi-access edge computing node load, and service processing efficiency;

[0043] (3) The terminal service is processed by the optimal multi-access edge computing node, and a node identifier is generated for the multi-access edge computing node, and the node identifier of the multi-access edge computing node that executes the terminal service is sent to the terminal for storage.

[0044] In this embodiment, the MEC node identifier is as follows: Figure 3 As shown, a total of 32 bits; specifically:

[0045] Bits 1 and 2 are reserved for future use.

[0046] The third bit indicates the state of the MEC node, including abnormal "unloading" state and normal "service" state;

[0047] Among them, "0" indicates that the MEC node is in an abnormal "uninstallation" state, for example: this MEC node will be maintained, decommissioned, etc., and will no longer receive tasks initiated by users; "1" indicates that the MEC node is in a normal "service" state, that is, it normally receives and processes services initiated by users.

[0048] The 4th bit indicates whether the MEC node is a dedicated MEC node;

[0049] Among them, 0 indicates that the MEC node is a general MEC node, and 1 indicates that the MEC node is a dedicated MEC node; for example, for some important parks, for data security considerations, it is necessary to configure a dedicated MEC node to serve only this park.

[0050] The 5th to 7th bits are used to distinguish different MEC sharing areas. Under normal circumstances, according to the four-color principle, 2 bits are sufficient for distinction. However, in this embodiment, considering the irregularity of the service range of the MEC sharing area, three bits are used to distinguish different MEC sharing areas.

[0051] Bits 8 to 12 are used to distinguish different MEC nodes in the MEC sharing area, and up to 32 MEC nodes can be distinguished.

[0052] Bits 13 to 32 are used to distinguish different users of MEC services, and can distinguish up to 1 million users.

[0053] In this embodiment, the delay includes but is not limited to the uplink and downlink transmission delay of task offloading, the computing task delay of multi-access edge computing nodes, the additional task migration delay caused by user movement, etc.;

[0054] The business processing benefits include but are not limited to operator business service charges / costs;

[0055] Costs include but are not limited to computing costs of multiple access edge computing nodes, network transmission costs, etc.

[0056] In this embodiment, the optimal multi-access edge computing node may be selected by, but is not limited to, the following methods:

[0057] (2-1) According to relevant strategies, different weights are assigned to latency, multi-access edge computing node load, and business processing efficiency;

[0058] In this embodiment, the operator formulates a weighting strategy according to the importance attached to the indicator, and the weight of each part is between 0 and 1, and the sum of the weights of each part is 1;

[0059] For example, the more important the part is, the higher the weight it is given. If you value the return, set the weight to 0.3. If the cost is relatively unimportant, you can set the weight to 0.05.

[0060] (2-2) The values ​​of the above indicators are evaluated for different MEC nodes in the MEC sharing area. It can be understood that the values ​​are between 0 and 1;

[0061] Specifically: for latency, the lower the latency, the higher the value when the demand is met; for efficiency, the higher the efficiency, the higher the value; for the load of multi-access edge computing nodes, the lower the load, the higher the value.

[0062] (2-3) Based on the weights and related values ​​of the above three indicators, calculate the comprehensive value of each MEC node in the MEC sharing area;

[0063] Specifically: comprehensive value = SUM (weight of each indicator * value of each indicator).

[0064] (2-4) Select the MEC node with the highest comprehensive value as the serving MEC node.

[0065] In this embodiment, the optimal MEC node can also be selected by using a genetic algorithm or a related neural network algorithm to obtain a MEC node with the highest comprehensive value as the serving MEC node.

[0066] In this embodiment, when a user initiates a service for the first time, the optimal multi-access edge computing node is selected to serve the user based on latency, multi-access edge computing node load, and service processing efficiency. After the service is completed, its own node identifier is sent to the user, and the user can save this target MEC identifier; then when the user initiates the service again, there is no need to select the optimal MEC node, and the task can be directly offloaded to the stored target MEC node for processing based on the saved MEC identifier.

[0067] In addition, when the stored target MEC node does not meet the business needs, the reselection of the MEC node is triggered, and the task is offloaded to the reselected MEC node for processing; similarly, after the task processing is completed, the reselected MEC node sends its own node identifier to the user, and the user saves this node identifier.

[0068] Based on this, when the user does not initiate a service for the first time, this embodiment proposes a multi-access edge computing node selection method for task offloading, such as Figure 4 As shown, the specific steps include:

[0069] (1) obtaining a terminal service, where the terminal service is not initiated for the first time;

[0070] (2) offloading the terminal service to the corresponding multi-access edge computing node according to the stored node identifier;

[0071] (3) Determine whether the target multi-access edge computing node to be offloaded meets the service requirements. If so, go to step (4); if not, go to step (5);

[0072] (4) The target multi-access edge computing node processes the terminal service;

[0073] (5) Select the optimal migration multi-access edge computing node based on latency, multi-access edge computing node load, and service processing efficiency;

[0074] (6) The target multi-access edge computing node offloads the terminal service to the migration multi-access edge computing node, which is then processed by the migration multi-access edge computing node;

[0075] (7) After the terminal service processing is completed, the migrating multi-access edge computing node sends its own node identifier to the user, and the user saves this node identifier as the subsequent target multi-access edge computing node.

[0076] This embodiment proposes to assist user task offloading through the node identification of the multi-access edge computing node. Each multi-access edge computing node is assigned a node identification. When the terminal user initiates a service, the task can be directly offloaded to the multi-access edge computing node corresponding to the node identification for processing through the stored node identification, thereby saving computing resources and reducing latency.

[0077] Example 2

[0078] This embodiment provides a task offloading node selection system, including:

[0079] The receiving module is configured to obtain the terminal service and determine whether the terminal service is initiated for the first time;

[0080] The initial service node selection module is configured to select the optimal multi-access edge computing node according to the latency, the multi-access edge computing node load and the service processing efficiency if the service is initiated for the first time, and to generate a node identifier for the multi-access edge computing node and store the node identifier of the multi-access edge computing node;

[0081] The non-initial service node selection module is configured to offload the terminal service to the corresponding multi-access edge computing node for processing according to the stored node identifier if it is not the first time to initiate the service.

[0082] In this embodiment, the system also includes a storage module configured to store received business needs, user mobility, channel quality, multi-access edge computing node load and other related information; and store unit computing unit cost, unit communication cost, operator service charges, related evaluation strategies or neural network algorithms.

[0083] In this embodiment, the system further includes an updating unit configured to update information in the storage module.

[0084] It should be noted that the above modules correspond to the steps described in Example 1, and the examples and application scenarios implemented by the above modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 1. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer executable instructions.

[0085] In further embodiments, there is also provided:

[0086] An electronic device includes a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method described in Embodiment 1 is performed. For the sake of brevity, it will not be described in detail here.

[0087] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0088] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0089] A computer-readable storage medium is used to store computer instructions, and when the computer instructions are executed by a processor, the method described in Example 1 is completed.

[0090] The method in Example 1 can be directly embodied as a hardware processor, or a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it is not described in detail here.

[0091] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in conjunction with this embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0092] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A task offloading node selection method, characterized in that: include: Obtain terminal services and determine whether the terminal services are initiated for the first time; If it is the first time to initiate, the optimal multi-access edge computing node is selected according to the latency, multi-access edge computing node load and business processing efficiency, and a node identifier is generated for the multi-access edge computing node, and the node identifier of the multi-access edge computing node is stored; If it is not the first time, the terminal service is unloaded to the corresponding multi-access edge computing node for processing according to the stored node identifier, including: Determine the corresponding target multi-access edge computing node according to the stored node identifier, and judge whether the target multi-access edge computing node meets the service requirements. If not, trigger the reselection of the multi-access edge computing node, and unload the terminal service to the reselected multi-access edge computing node for processing, and save the node identifier of the reselected multi-access edge computing node; The delay includes the uplink and downlink transmission delay of task offloading, the computing task delay of multi-access edge computing nodes and the task migration delay of terminal mobility; the service processing benefits include the service charges and costs of operators; the costs include the computing costs and network transmission costs of multi-access edge computing nodes; The optimal multi-access edge computing node selection method specifically includes the following steps: (1) Different weights are assigned to latency, multi-access edge computing node load, and service processing efficiency; (2) Evaluate the values ​​of latency, multi-access edge computing node load, and service processing efficiency indicators for different multi-access edge computing nodes in the multi-access edge computing sharing area, with values ​​between 0 and 1; (3) Based on the weights and values ​​of the above three indicators, calculate the comprehensive value of each multi-access edge computing node in the multi-access edge computing sharing area; Specifically: comprehensive value = SUM (weight of each indicator * value of each indicator); (4) Select the multi-access edge computing node with the highest comprehensive value as the multi-access edge computing node for the service.

2. A task offloading node selection method as claimed in claim 1, characterized in that: The node identifier has a total of 32 bits, which respectively represent the reserved bit, the multi-access edge computing node status, the multi-access edge computing node type, different MEC sharing areas, different multi-access edge computing nodes in the MEC sharing area, and different users under the multi-access edge computing node.

3. A task offloading node selection method as claimed in claim 2, characterized in that: The state of the multi-access edge computing node includes an abnormal unloading state and a normal service state, which are represented by 0 and 1 respectively.

4. A task offloading node selection method as claimed in claim 2, characterized in that: The multi-access edge computing node types include general multi-access edge computing nodes and dedicated multi-access edge computing nodes, which are represented by 0 and 1 respectively.

5. A task offloading node selection method as claimed in claim 2, characterized in that: The node identifier has a total of 32 bits, of which bits 1-2 are reserved, bit 3 indicates the multi-access edge computing node state, bit 4 indicates the multi-access edge computing node type; bits 5-7 indicate different MEC shared areas; bits 8-12 indicate different multi-access edge computing nodes within the MEC shared area, and bits 13-32 indicate different users under the multi-access edge computing node.

6. A task offloading node selection system, characterized in that: include: The receiving module is configured to obtain the terminal service and determine whether the terminal service is initiated for the first time; The initial service node selection module is configured to select the optimal multi-access edge computing node according to the latency, the multi-access edge computing node load and the service processing efficiency if the service is initiated for the first time, and to generate a node identifier for the multi-access edge computing node and store the node identifier of the multi-access edge computing node; The non-initial service node selection module is configured to offload the terminal service to the corresponding multi-access edge computing node for processing according to the stored node identifier if it is not the first time to initiate the service, specifically including: Determine the corresponding target multi-access edge computing node according to the stored node identifier, and judge whether the target multi-access edge computing node meets the service requirements. If not, trigger the reselection of the multi-access edge computing node, and unload the terminal service to the reselected multi-access edge computing node for processing, and save the node identifier of the reselected multi-access edge computing node; The delay includes the uplink and downlink transmission delay of task offloading, the computing task delay of multi-access edge computing nodes and the task migration delay of terminal mobility; the service processing benefits include the service charges and costs of operators; the costs include the computing costs and network transmission costs of multi-access edge computing nodes; The optimal multi-access edge computing node selection method specifically includes the following steps: (1) Different weights are assigned to latency, multi-access edge computing node load, and service processing efficiency; (2) Evaluate the values ​​of latency, multi-access edge computing node load, and service processing efficiency indicators for different multi-access edge computing nodes in the multi-access edge computing sharing area, with values ​​between 0 and 1; (3) Based on the weights and values ​​of the above three indicators, calculate the comprehensive value of each multi-access edge computing node in the multi-access edge computing sharing area; Specifically: comprehensive value = SUM (weight of each indicator * value of each indicator); (4) Select the multi-access edge computing node with the highest comprehensive value as the multi-access edge computing node for the service.

7. An electronic device, characterized in that: The method comprises a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method according to any one of claims 1 to 5 is completed.

8. A computer-readable storage medium, characterized in that: Used to store computer instructions, which, when executed by a processor, complete the method described in any one of claims 1 to 5.

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