Research on intelligent computing offloading model based on reputation value in mobile edge computing

Jin QI; Hairong SUN; Kun GONG; Bin XU; Shunyi ZHANG; Yanfei SUN

doi:10.11959/j.issn.1000-436x.2020105

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Research on intelligent computing offloading model based on reputation value in mobile edge computing

Papers | 更新时间：2024-06-05

- Research on intelligent computing offloading model based on reputation value in mobile edge computing
- Journal on Communications Vol. 41, Issue 7, Pages: 141-151(2020)
- 作者机构：
  
  1. 南京邮电大学物联网学院，江苏南京 210003
  2. 南京邮电大学自动化学院、人工智能学院，江苏南京 210003
  3. 南京邮电大学计算机学院，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61802208);The National Natural Science Foundation of China(61772286);The Postdoctoral Science Foundation of China(2019M651923);The Natural Science Foundation of Jiangsu Province(BK20191381);The Primary Research ＆ Development Plan of Jiangsu Province(BE2019742)
- DOI：10.11959/j.issn.1000-436x.2020105
  CLC： TP393
- Online First：2020-07，
  
  Published：25 July 2020
- 稿件说明：
移动端阅览
Jin QI, Hairong SUN, Kun GONG, et al. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on Communications, 2020, 41(7): 141-151.
DOI：

Jin QI, Hairong SUN, Kun GONG, et al. Research on intelligent computing offloading model based on reputation value in mobile edge computing[J]. Journal on Communications, 2020, 41(7): 141-151. DOI： 10.11959/j.issn.1000-436x.2020105.

摘要

针对移动边缘计算环境下，爆炸式增长的物联网智能移动终端处理计算密集型和时延敏感型新兴移动应用时，面临的高时延、高能耗和低可靠性等问题，提出综合考虑时延和能耗的卸载决策模型和基于信誉值的计算资源博弈分配模型，并分别利用改进粒子群算法和拉格朗日乘数法求解。仿真结果表明，所提方法可满足新兴智能应用对于低时延、低能耗和高可靠性的服务需求，可有效实现计算卸载资源的整体优化配置。

Abstract

Aiming at the problem of high-latency

high-energy-consumption

and low-reliability mobile caused by computing-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminals in the mobile edge computing environment

an offload decision-making model where delay and energy consumption were comprehensively included

and a computing resource game allocation model based on reputation that took into account was proposed

then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.Simulation results show that the proposed method can meet the service requirements of emerging intelligent applications for low latency

low energy consumption and high reliability

and effectively implement the overall optimized allocation of computing offload resources.

关键词

Keywords

references

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