Multi-access edge calculation node selection method and system based on regional pool networking

Abstract

The invention discloses a multi-access edge calculation node selection method and a system based on regional pool networking. The method comprises the following steps: constructing a multi-access edge calculation node regional pool; obtaining service processing time delay according to the communication time delay between the terminal and the multi-access edge calculation node, the multi-access edge calculation node calculation time delay, the terminal calculation time delay and the migration time delay of terminal switching; obtaining service processing energy consumption according to the local calculation energy consumption, the task transmission energy consumption and the multi-access edge calculation node calculation energy consumption; obtaining service benefits according to the service processing cost and the income after service processing; and obtaining an optimal multi-access edge calculation node for processing the terminal service according to the service processing time delay, the service processing energy consumption, the service benefit and the load of the multi-access edge calculation node. The selection of the optimal multi-access edge calculation node is considered from the aspects of service processing delay, service processing energy consumption, service benefits and multi-access edge calculation node loads, the dimensions are considered more comprehensively, and the service processing efficiency and benefits are improved.

Description

technical field [0001] The present invention relates to the technical field of mobile communication, in particular to a method and system for selecting multi-access edge computing nodes based on regional pool networking. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] Multi-access edge computing can provide network, computing, and storage services close to users. It can not only realize localized processing of traffic, reduce the traffic impact on the transmission network, but also provide a low-latency application operating environment. At present, the application of mobile edge computing will extend to areas such as autonomous driving, AR / VR, cloud games, and industrial automatic control. [0004] The research on multi-access edge computing mainly focuses on the independent deployment of multi-access edge computing node MEC, that is, wh...

AI Technical Summary

Problems solved by technology

[0006] (1) When the user moves, it will increase the service processing delay and cost; for example, the user UE1 offloads the task to the MEC1 through the access point 1 for processing, and the user UE1 moves to another access point 2 when the task is not processed However, since access point 2 is not connected to MEC1, the intercommunication with MEC1 cannot be realized through access point 2, and MEC1 needs to migrate unfinished tasks to MEC2 through the core network to continue processing; however, due to the core network element Generally located in large data centers, far away from users, resulting in greatly increased business processing delays and processing costs

[0007] (2) In considering redundancy scenarios, the utilization rate of MEC is not high

[0008] (3) When considering selecting the optimal MEC for task offloading, the alternative MEC can only choose the MEC connected to the user's current access point, which cannot achieve the regional optimal

Images