Task Offloading Scheme Based on Comprehensive Trust Evaluation in Edge Computing

XIONG Xiao-feng; HUANG Chun-lan; YUE Guang-xue; DAI Ya-sheng; YANG Xiao-hui; YANG Zhong-ming

doi:10.12263/DZXB.20210296

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Task Offloading Scheme Based on Comprehensive Trust Evaluation in Edge Computing

PAPERS | 更新时间：2025-12-08

- Task Offloading Scheme Based on Comprehensive Trust Evaluation in Edge Computing
- ACTA ELECTRONICA SINICA Vol. 50, Issue 9, Pages: 2134-2145(2022)
- 作者机构：
  
  1.江西理工大学理学院，江西赣州 341000
  2.嘉兴学院信息科学与工程学院，浙江嘉兴 314001
- 作者简介：
- 基金信息：
- DOI：10.12263/DZXB.20210296
  CLC： TP393
- Received：01 March 2021，
  
  Revised：2021-08-10，
  
  Published：25 September 2022
- 稿件说明：
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熊小峰,黄淳岚,乐光学等.边缘计算中基于综合信任评价的任务卸载策略[J].电子学报,2022,50(09):2134-2145.

XIONG Xiao-feng,HUANG Chun-lan,YUE Guang-xue,et al.Task Offloading Scheme Based on Comprehensive Trust Evaluation in Edge Computing[J].ACTA ELECTRONICA SINICA,2022,50(09):2134-2145.
熊小峰,黄淳岚,乐光学等.边缘计算中基于综合信任评价的任务卸载策略[J].电子学报,2022,50(09):2134-2145. DOI： 10.12263/DZXB.20210296.

XIONG Xiao-feng,HUANG Chun-lan,YUE Guang-xue,et al.Task Offloading Scheme Based on Comprehensive Trust Evaluation in Edge Computing[J].ACTA ELECTRONICA SINICA,2022,50(09):2134-2145. DOI： 10.12263/DZXB.20210296.

摘要

针对边缘计算中存在虚假欺骗、搭便车等不良行为导致资源浪费和卸载服务低效的问题，提出一种基于综合信任评价的任务卸载（Task Offloading scheme based on Comprehensive Trust Evaluation， TOCTE）策略. 建立节点信任遗忘函数，以任务真实性和节点卸载协作行为特征为约束，构建节点间卸载请求和协作信任评价模型，识别并过滤网络中的虚假任务和不良协作节点. 设计搜索发现概率优化粒子群算法，规避节点重复利用引起的节点过载，提高边缘计算任务卸载效率和资源有效利用. 仿真实验表明，TOCTE策略模型真实任务执行成功率达到59.22%，资源损耗率最低达到6.35%，能有效抑制和过滤虚假任务，降低资源损耗.

Abstract

In edge computing

waste of resources and inefficient offloading services are key issues caused by bad behaviors such as false deception and free-riding. To address the selfishness key issues

a task offloading scheme based on comprehensive trust evaluation(TOCTE) is proposed. By establishing nodes trust forgetting function

and taking task authenticity and nodes offloading cooperative behavior characteristics as constraints

the offloading request and cooperative trust evaluation models between nodes are constructed to identify and filter false tasks and bad cooperative nodes in the network. Particle swarm algorithm based on search discovery probability is designed to avoid the node overload caused by the repeatedly utilization of nodes

improve task offloading efficiency and resource utilization of edge computing. The simulation results show that the real task execution success rate and the lowest resource consumption rate of TOCTE are 59.22% and 6.35%. TOCTE model can effectively suppress and filter false tasks

and reduce resource consumption.

关键词

Keywords

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