基于时延和能耗约束的感知数据协作卸载策略研究

袁培燕; 邵赛珂; 魏然; 张俊娜; 赵晓焱

doi:10.11959/j.issn.2096-3750.2023.00324

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基于时延和能耗约束的感知数据协作卸载策略研究

理论与技术 | 更新时间：2024-08-16

- 基于时延和能耗约束的感知数据协作卸载策略研究
- Research on the cooperative offloading strategy of sensory data based on delay and energy constraints
- 物联网学报 2023年7卷第1期页码：109-117
- 作者机构：
  
  1. 河南师范大学计算机与信息工程学院，河南新乡 453007
  2. 河南师范大学教学资源与教育质量评估大数据河南省工程实验室，河南新乡 453007
- 作者简介：
  
  [ "袁培燕（1978- ），男，博士，河南师范大学教授，主要研究方向为边缘计算与群智感知、移动自组织与机会网络、网络大数据等" ]
  [ "邵赛珂（1998- ），男，河南师范大学硕士生，主要研究方向为移动边缘计算" ]
  [ "魏然（1978- ），男，河南师范大学工程师，主要研究方向为数据库与软件开发" ]
  [ "张俊娜（1979- ），女，博士，河南师范大学副教授，主要研究方向为移动边缘计算、服务计算等" ]
  [ "赵晓焱（1981- ），女，博士，河南师范大学副教授，主要研究方向为移动边缘计算、D2D通信、物联网等" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(62072159);国家自然科学基金资助项目;The National Natural Science Foundation of China(U1804164);国家自然科学基金资助项目;The National Natural Science Foundation of China(61902112);河南省教育厅重点项目;The Key Project of the Education Department of Henan Province(19A510015);河南省教育厅重点项目;The Key Project of the Education Department of Henan Province(20A520019);河南省教育厅重点项目;The Key Project of the Education Department of Henan Province(20A520020)
- DOI：10.11959/j.issn.2096-3750.2023.00324
  中图分类号： TP391
- 纸质出版日期：2023-03-30，
  
  网络出版日期：2023-03，
- 稿件说明：
移动端阅览
袁培燕, 邵赛珂, 魏然, 等. 基于时延和能耗约束的感知数据协作卸载策略研究[J]. 物联网学报, 2023,7(1):109-117.

PEIYAN YUAN, SAIKE SHAO, RAN WEI, et al. Research on the cooperative offloading strategy of sensory data based on delay and energy constraints. [J]. Chinese journal on internet of things, 2023, 7(1): 109-117.
袁培燕, 邵赛珂, 魏然, 等. 基于时延和能耗约束的感知数据协作卸载策略研究[J]. 物联网学报, 2023,7(1):109-117. DOI： 10.11959/j.issn.2096-3750.2023.00324.

PEIYAN YUAN, SAIKE SHAO, RAN WEI, et al. Research on the cooperative offloading strategy of sensory data based on delay and energy constraints. [J]. Chinese journal on internet of things, 2023, 7(1): 109-117. DOI： 10.11959/j.issn.2096-3750.2023.00324.

摘要

研究了物联网感知数据边缘卸载问题，即多个边缘节点相互协作，将原本需要发送给云中心的感知数据全部或部分卸载，以保护数据隐私与提升用户体验。在协作卸载过程中，感知数据传输以及边缘节点之间的信息交互会消耗系统资源，产生协作代价。如何在保持较低协作代价的基础上提高感知数据的卸载比例是一个具有挑战性的问题。首先，将该问题表述为一个满足网络时延和系统能耗约束的感知数据卸载比例和协作规模联合优化问题。其次，提出了一种基于约束投影和变量分裂的分布式交替方向乘子法（ADMM

alternating direction method of multipliers）进行求解。最后，使用MATLAB进行仿真实验，数值结果表明，与分布式优化算法（DOA

distributed optimization algorithm）、公平合作算法（FCA

fairness cooperation algorithm）和多子任务到多服务器卸载方案（MTMS

multi-subtasks-to-multi-servers offloading scheme）相比，所提方法在网络时延和能耗上均有较大优化。

Abstract

The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center

which protects data privacy and improves user experience.In the process of cooperative offloading

the transmission of the sensing data and the information exchange among edge servers will consume system resources

resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently

a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally

simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA)

the distributed optimization algorithm (DOA)

and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.

关键词

协同边缘计算数据卸载系统能耗网络时延分布式ADMM

Keywords

collaborative edge computingdata offloadingsystem energy consumptionnetwork delaydistributed ADMM

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