传输时限约束下的能量收集无线传感器网络多址接入优化

杨澳钦; 宫傲宇; 房婷; 邓磊; 李强; 张一晋

doi:10.11959/j.issn.2096-3750.2022.00283

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传输时限约束下的能量收集无线传感器网络多址接入优化

理论与技术 | 更新时间：2024-06-05

- 传输时限约束下的能量收集无线传感器网络多址接入优化
- Optimization of multiple access in the energy harvesting wireless sensor network with delivery deadline constraint
- 物联网学报 2022年6卷第3期页码：58-70
- 作者机构：
  
  1. 南京理工大学电子工程与光电技术学院，江苏南京 210094
  2. 洛桑联邦理工学院计算机与通信科学学院，瑞士洛桑 1015
  3. 深圳大学电子与信息工程学院，广东深圳 518060
  4. 鹏城实验室，广东深圳 518055
- 作者简介：
  
  [ "杨澳钦（1999- ），女，南京理工大学硕士生，主要研究方向为无线网络协议设计和优化" ]
  [ "宫傲宇（1997- ），男，洛桑联邦理工学院硕士生，主要研究方向为无线网络协议设计及优化" ]
  [ "房婷（1998- ），女，南京理工大学硕士生，主要研究方向为无线网络协议设计和优化" ]
  [ "邓磊（1989- ），男，博士，深圳大学助理教授，主要研究方向为时延受限网络通信" ]
  [ "李强（1973- ），男，博士，鹏城实验室正高级工程师，主要研究方向为物联网与5G/B5G" ]
  [ "张一晋（1982- ），男，博士，南京理工大学教授，主要研究方向为序列设计、无线网络与人工智能" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(62071236);国家自然科学基金资助项目;The National Natural Science Foundation of China(61902256);中央高校基本科研业务费专项资金资助项目;The Fundamental Research Funds for the Central Universities(30920021127);鹏城实验室重点项目;The Major Key Project of PCL(PCL2021A15)
- DOI：10.11959/j.issn.2096-3750.2022.00283
  中图分类号： TN911
- 纸质出版日期：2022-09-30，
  
  网络出版日期：2022-09，
- 稿件说明：
移动端阅览
杨澳钦, 宫傲宇, 房婷, 等. 传输时限约束下的能量收集无线传感器网络多址接入优化[J]. 物联网学报, 2022,6(3):58-70.

AOQIN YANG, AOYU GONG, TING FANG, et al. Optimization of multiple access in the energy harvesting wireless sensor network with delivery deadline constraint. [J]. Chinese journal on internet of things, 2022, 6(3): 58-70.
杨澳钦, 宫傲宇, 房婷, 等. 传输时限约束下的能量收集无线传感器网络多址接入优化[J]. 物联网学报, 2022,6(3):58-70. DOI： 10.11959/j.issn.2096-3750.2022.00283.

AOQIN YANG, AOYU GONG, TING FANG, et al. Optimization of multiple access in the energy harvesting wireless sensor network with delivery deadline constraint. [J]. Chinese journal on internet of things, 2022, 6(3): 58-70. DOI： 10.11959/j.issn.2096-3750.2022.00283.

摘要

随着能量收集无线传感器网络在环境监测、工业自动化、战场侦察等实时通信场景的广泛应用，多址接入需要同时考虑数据分组严格的传输时限特性以及传感器节点的能量收集特性。由于节点互干扰、传输紧迫性及能量储存度等因素的固有耦合，此多址接入的设计和优化相比于仅需考虑数据分组到达特性的传统多址接入具有更大挑战性。首先，设计各节点接入行为依赖于全局传输紧迫性和剩余能量的集中式接入协议；然后，考虑集中式接入具有难以承受的控制开销，设计各节点接入概率仅依赖于本地传输紧迫性和剩余能量的分布式接入协议。以最大化网络吞吐率为优化目标，使用马尔可夫决策过程对集中式接入分别进行考虑所有数据分组信息的完整建模和仅考虑队首数据分组信息的简化建模，并基于逆向归纳算法求解两种建模的最优集中式策略；最后，使用分布式马尔可夫决策过程对分布式接入协议进行简化建模，并基于马尔可夫策略搜索方法提出ε-最优分布式策略。仿真结果验证了简化建模的有效性和所提出策略相较于其他策略的性能优越性。

Abstract

With the wide application of the energy harvesting wireless sensor network (WSN) in many real-time communication scenarios

such as environmental monitoring

industrial automation and battlefield surveillance

the multiple access of such WSN needs to take into account both the delivery deadline constraint of data packets and the energy harvesting dynamics of sensor nodes.Due to the inherent decoupling of interference

delivery urgency and remaining energy

the design and optimization of such multiple access are more challenging than that of traditional multiple access that only needs to take into account the packet traffic pattern.A centralized access scheme was designed with the access actions relying on the global knowledge of current delivery urgency and remaining energy.And then

to avoid the costly overhead in the centralized access

a decentralized access scheme was designed with the access probabilities merely relying on the local knowledge of delivery urgency and remaining energy.Under the objective of maximizing the network throughput

the centralized access schemes were formulated with complete and simplified knowledge as two Markov decision processes (MDPs)

respectively

and the backward induction algorithm was used to obtain optimal centralized policies for these MDPs.Furthermore

the decentralized access was formulated with simplified knowledge as a decentralized MDP

and the Markov policy search was used to propose an ε-optimal decentralized policy.Simulations under a wide range of network configurations were provided to verify the effectiveness of the simplified modeling and demonstrate the performance advantage of the proposed polices.

关键词

传输时限能量收集马尔可夫决策过程多址接入

Keywords

delivery deadlineenergy harvestingMarkov decision processmultiple access

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