Task unloading and resource allocation method based on mobile edge computing in Internet of Vehicles

Abstract

The invention discloses a task unloading and resource allocation method based on mobile edge computing in the Internet of Vehicles. The method comprises the following specific steps: establishing an Internet of Vehicles communication scene comprising vehicle-to-vehicle V2V and vehicle-to-infrastructure V2I communication; clustering the vehicle nodes in the scene, and dividing the vehicle nodes into a V2I user cluster and a V2V user cluster; for a V2V user cluster in the scene, dividing, pairing and optimizing V2V request nodes and service nodes in the V2V user cluster; calculating the total delay of task processing of all nodes in the scene; the optimization problem model is established by taking minimization of the total delay of vehicle task processing in the Internet of Vehicles systemas a target and combining constraint conditions, and the optimization problem model is solved by utilizing a quantum particle swarm algorithm to obtain a channel of the Internet of Vehicles system, computing resource allocation and a power allocation strategy of each vehicle node. According to the method, the MEC-based task unloading and resource allocation problem in the Internet of Vehicles environment is solved with lower complexity.

Description

technical field [0001] The invention relates to the technical field of task offloading and resource allocation of mobile edge computing in the Internet of Vehicles, in particular to a method for task offloading and resource allocation based on mobile edge computing in the Internet of Vehicles. Background technique [0002] With the continuous development of mobile network technology, people's research on vehicle communication is deepening. Utilizing highly reliable, low-latency wireless communication services provided by vehicle-to-everything (V2X) can improve road safety and enhance the driving experience. Common car networking systems include information exchange paths such as vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V). Vehicle request tasks can be divided into business and entertainment categories and security categories. Business and entertainment requests involve a large amount of data exchange; security requests have high requirements for latency. ...

AI Technical Summary

Problems solved by technology

In the research process of the technical solution of the present invention, at least it is found that the disadvantage of the existing technology is that it does not consider the key issue of how D2D users establish pairing in D2D communication, but the default D2D pairing has been determined

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