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

A technology for computing tasks and edge computing, applied in the field of mobile communications, can solve problems such as large energy consumption, reduce energy consumption overhead and achieve the effect of effectiveness

Pending Publication Date: 2022-06-17
CHONGQING UNIV OF POSTS & TELECOMM
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The power of the edge server increases quadratically with the CPU speed. When th

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  • Task unloading method based on mobile edge computing in Internet of Vehicles
  • Task unloading method based on mobile edge computing in Internet of Vehicles
  • Task unloading method based on mobile edge computing in Internet of Vehicles

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[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] A task offloading method based on mobile edge computing in the Internet of Vehicles, such as figure 2 As shown, the method includes: constructing a joint unloading model of multi-edge servers; obtaining unloading tasks of vehicles, and calculating a resource allocation scheme for task unloading by using a resource allocation method based on equivalent maximum delay tolerance; The unloading task is optimized, and the task unlo...

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Abstract

The invention belongs to the technical field of mobile communication, and particularly relates to a task unloading method based on mobile edge computing in the Internet of Vehicles, which comprises the following steps: constructing a multi-edge server joint unloading model; obtaining an unloading task of the vehicle, and constructing an unloading base station selection vector according to the unloading task of the vehicle; calculating load and energy consumption for task unloading according to the unloading base station selection vector by adopting a resource allocation method based on equivalent maximum tolerant time delay; taking the energy consumption as an adaptive function, and performing iterative optimization on an unloading task of the vehicle by adopting a genetic algorithm to obtain an unloading base station selection scheme; optimizing a task unloading strategy by using reinforcement learning according to an unloading base station selection scheme to obtain a task unloading ratio and unloading power; task unloading is completed according to the selected unloading base station, the formulated unloading ratio and the formulated unloading power; according to the method, the total energy consumption overhead of the system is effectively reduced, and the effectiveness of task unloading and resource allocation of the Internet of Vehicles is realized.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and in particular relates to a task offloading method based on mobile edge computing in the Internet of Vehicles. Background technique [0002] New mobile IoT applications such as autonomous driving and virtual reality require the execution of computationally intensive tasks with stringent latency requirements, which are challenging to complete in a timely manner given the limited processing power of mobile devices. Cloud computing can reduce the resource constraints of mobile devices through computational offloading, but its main challenge is the high latency caused by the continuous close communication between vehicles and cloud servers. In order to meet the requirements of low latency and high performance, mobile edge computing (MEC) has emerged as a practical solution, which can greatly alleviate the The resource limit of the vehicle. Due to the diversification of task types, m...

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Application Information

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IPC IPC(8): H04W4/44H04W28/08G06N3/12
CPCH04W4/44H04W28/0925H04W28/0917G06N3/126
Inventor 林峰胡强彭贻蒋建春
Owner CHONGQING UNIV OF POSTS & TELECOMM
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