A Load Balancing Method for Edge Computing of Internet of Vehicles

Abstract

The invention relates to a load balancing method for edge computing of the Internet of Vehicles, which belongs to the field of the Internet of Vehicles. Including: MEC server initialization; MEC server periodically updates index weights, calculates server performance and load rate, judges server load status and uploads relevant information to dispatch center; dispatch center receives information uploaded by each MEC server, and The information is stored and updated; if the dispatch center receives the task migration request from the server, it classifies the servers, screens out the servers that can receive the migration task, and calculates the transfer probability of each server; the dispatch center arranges the task migration according to the transfer probability , the eNodeB receives the scheduling arrangement of the dispatching center, and transmits the task to the target eNodeB through the X2 port. After the task calculation is completed, the calculation result is sent back; waiting for the next cycle. The invention can effectively improve the load balancing degree of the server cluster and shorten the task completion time.

Description

technical field [0001] The invention belongs to the field of the Internet of Vehicles, and relates to a load balancing method for edge computing of the Internet of Vehicles. Background technique [0002] With the continuous development of the Internet of Vehicles, C-V2X (Cellular-Vehicle to Everything) technology based on cellular communication systems and MEC (Mobile Edge Computing) technology based on multi-access edge computing are getting closer and closer. C-V2X technology can greatly reduce The cost of deploying autonomous driving and Internet of Vehicles in the future, while MEC technology migrates computing, storage, and business service capabilities to the edge of the network close to the terminal or data source, and has the characteristics of localized processing and distributed deployment. [0003] The integration of C-V2X technology and MEC technology can realize the collaborative interaction of "human-vehicle-road-cloud". However, on the road, due to the uneven...

AI Technical Summary

Problems solved by technology

[0006] The traditional load balancing method focuses on exploring the task allocation strategy, while ignoring issues such as when the server performs task allocation and how to accurately judge the server's operating status. These issues have a great impact on the allocation of subsequent tasks, especially in the Internet of Vehicles environment. Due to the mobility of vehicles, the load status of each MEC server is quite different, which can easily lead to problems such as low cluster load balance and low resource utilization.

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