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A method and system for joint computing resource allocation and unloading decision-making in MEC

A technology for computing resources and decision-making, applied in transmission systems, electrical components, etc., can solve problems such as less joint optimization

Active Publication Date: 2022-06-24
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are many studies on edge computing offloading algorithms and resource allocation in academia, but most of them are optimized for a single problem, and the joint optimization of the two is relatively rare.

Method used

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  • A method and system for joint computing resource allocation and unloading decision-making in MEC
  • A method and system for joint computing resource allocation and unloading decision-making in MEC
  • A method and system for joint computing resource allocation and unloading decision-making in MEC

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Experimental program
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Embodiment 1

[0086] like figure 1 As shown, a method and system for joint computing resource allocation and offloading decision in MEC, comprising the following steps:

[0087] Step 1: N vehicles each generate a computationally intensive and time-sensitive computational task per unit time, and the computational task of vehicle i is defined as s i ={H i ,Z i ,T i MAX}, where H i Indicates the data size of the current task i, Z i Represents the number of CPU revolutions required to complete the task i, T i MAX Indicates that the current task can tolerate the maximum delay; task i is generated by vehicle i, so task i and vehicle i share i to represent;

[0088] Step 2: The computing task can choose the two modes of local computing or offloading to the edge computing server for computing;

[0089] use a i ∈{0,1} represents the choice of task calculation mode, when a i =0 means that vehicle i selects the local calculation mode, a i When = 1, it means that the vehicle i chooses to of...

Embodiment 2

[0166] Step 1: Build a computing offloading system in an edge network environment. There are 1 macro base station and 1 micro base station in a square area of ​​1Km*1Km. The communication range between the macro base station and the micro base station is 1.5Km and 1Km. Take B=2MHz for each channel bandwidth, the transmit power p of the micro base station s =30dbm, the transmit power p of the macro base station m =46dbm, Gaussian white noise σ 2 =-147dbm, the interference between the macro base station and the micro base station I=100σ 2 , the channel attenuation model of the user is u=127+30logd (d is the distance between the user and the base station), and the calculation method of the channel gain between the micro base station and the macro base station and the vehicle i is G i =10 -u / 10 .

[0167] Step 2: Randomly distribute 150 vehicles, the calculation frequency on each vehicle is a random value between 0.8 and 1GHz, and each vehicle will generate a calculation task ...

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Abstract

The invention belongs to the technical field of mobile edge computing, and specifically relates to a method and system for joint computing resource allocation and offloading decision-making in MEC; a computing offloading system in an edge network environment is constructed, including a macro base station, a micro base station, and a cloud service center ;Establish the vehicle task model; Discuss the calculation models of six unloading methods, calculate the energy consumption and time delay under the six methods, and transform the energy consumption and time delay problem into the optimization problem of overhead; use the greedy algorithm to unload the scheme The selection and unloading decision is substituted into the optimization problem, and the resource allocation scheme is obtained by using the convex optimization algorithm to solve it. Under the system studied in the present invention, the joint optimization problem of computing resources and unloading decision is formalized, and the problem of resource allocation and unloading decision under the edge network is solved.

Description

technical field [0001] The invention belongs to the technical field of mobile edge computing, and in particular relates to a method and system for joint computing resource allocation and offloading decision in MEC. Background technique [0002] As the wave of intelligence sweeps the world, vehicles are becoming more and more intelligent. In smart cars, there are a large number of computing-intensive tasks. These tasks not only require large amounts of computation, but also require low latency and low energy consumption, and the traditional Internet of Vehicles cannot meet these two requirements. [0003] The mobile edge computing of the Internet of Vehicles can effectively promote the intelligent and unmanned vehicles, and at the same time, it can also improve the shortcomings of the traditional Internet of Vehicles, such as high latency, high energy consumption, and excessive server load. At present, there are many academic researches on edge computing offloading algorithm...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L67/12H04L67/10H04L41/0893
CPCH04L67/12H04L67/10H04L41/0893
Inventor 丛玉良孙淑娴薛科孙闻晞赵欣宇
Owner JILIN UNIV