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

doi:10.11959/j.issn.2096-3750.2022.00283

物联网学报 ›› 2022, Vol. 6 ›› Issue (3): 58-70.doi: 10.11959/j.issn.2096-3750.2022.00283

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¹, 宫傲宇², 房婷¹, 邓磊³, 李强⁴, 张一晋¹

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

修回日期:2022-06-24 出版日期:2022-08-05 发布日期:2022-08-08
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
基金资助:
国家自然科学基金资助项目(62071236);国家自然科学基金资助项目(61902256);中央高校基本科研业务费专项资金资助项目(30920021127);鹏城实验室重大攻关项目(PCL2021A15)

Optimization of multiple access in the energy harvesting wireless sensor network with delivery deadline constraint

Aoqin YANG¹, Aoyu GONG², Ting FANG¹, Lei DENG³, Qiang LI⁴, Yijin ZHANG¹

¹ School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
² School of Computer and Communication Sciences, école Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
³ College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, China
⁴ Peng Cheng Laboratory, Shenzhen 518055, China

Revised:2022-06-24 Online:2022-08-05 Published:2022-08-08
Supported by:
The National Natural Science Foundation of China(62071236);The National Natural Science Foundation of China(61902256);The Fundamental Research Funds for the Central Universities(30920021127);The Major Key Project of Peng Cheng Laboratory(PCL2021A15)

摘要/Abstract

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。

关键词: 传输时限, 能量收集, 马尔可夫决策过程, 多址接入

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.

Key words: delivery deadline, energy harvesting, Markov decision process, multiple access

中图分类号:

TN911

杨澳钦, 宫傲宇, 房婷, 邓磊, 李强, 张一晋. 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, Lei DENG, Qiang LI, Yijin ZHANG. 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.

图/表 8

图1

图2

图3

表1

策略计算复杂度及观测需求对比"

算法	复杂度	观测需求
最优集中式策略（完整建模）	$O ([2^{D} (E + 1)]^{2 N} \cdot 2^{N})$	每个时隙均为完全观测
最优集中式策略（简化建模）	$O ([(D + 1) (E + 1)]^{2 N} \cdot 2^{N})$	每个时隙均为完全观测
10^-7最优分布式策略	$O ((1 / Δ a + 1)^{(D + 1) (E + 1) N})$	仅第一时隙为完全观测其余时隙为部分观测
最优静态策略	$O (1)$	无须观测

表1

图4

图5

图6

图7

参考文献 30

[1]	QUINTERO V L , ESTEVEZ C , ORCHARD M E ,et al. Improvements of energy-efficient techniques in WSNs,a MAC-protocol approach[J]. IEEE Communications Surveys ＆ Tutorials, 2018,21(2): 1188-1208.
[2]	HASSAN G , HASSANEIN H S . MoT,a deterministic latency MAC protocol for mission-critical IoT applications[C]// Proceedings of 2018 14th International Wireless Communications ＆ Mobile Computing Conference (IWCMC). Piscataway,IEEE Press, 2018: 588-593.
[3]	FARAG H , GIDLUND M , ?STERBERG P , . A delay-bounded MAC protocol for mission- and time-critical applications in industrial wireless sensor networks[J]. IEEE Sensors Journal, 2018,18(6): 2607-2616.
[4]	THOMAS D , SHANKARAN R , ORGUN M ,et al. Energy-efficient military surveillance,coverage meets connectivity[J]. IEEE Sensors Journal, 2019,19(10): 3902-3911.
[5]	LUVISOTTO M , PANG Z B , DZUNG D . High-performance wireless networks for industrial control applications,new targets and feasibility[J]. Proceedings of the IEEE, 2019,107(6): 1074-1093.
[6]	王哲, 李陶深, 叶进 ,等. 基于不确定理论的能量收集可靠性建模及规划[J]. 通信学报, 2018,39(5): 166-176.
	WANG Z , LI T S , YE J ,et al. Reliability modeling and planning of energy harvesting based on uncertainty theory[J]. Journal on Communications, 2018,39(5): 166-176.
[7]	LU X , WANG P , NIYATO D ,et al. Wireless networks with RF energy harvesting,a contemporary survey[J]. IEEE Communications Surveys＆ Tutorials, 2014,17(2): 757-789.
[8]	BAE Y H . Analysis of optimal random access for broadcasting with deadline in cognitive radio networks[J]. IEEE Communications Letters, 2013,17(3): 573-575.
[9]	ZHANG Y J , GUAN F Y , LO Y H . Coding-based slotted ALOHA for broadcasting multislot messages with delivery deadline[J]. IEEE Transactions on Vehicular Technology, 2018,67(8): 7882-7886.
[10]	ZHANG Y J , LO Y H , SHU F ,et al. Achieving maximum reliability in deadline-constrained random access with multiple-packet reception[J]. IEEE Transactions on Vehicular Technology, 2019,68(6): 5997-6008.
[11]	BAE Y H . Optimal retransmission-based broadcasting under delivery deadline constraint[J]. IEEE Communications Letters, 2015,19(6): 1041-1044.
[12]	DENG L , DENG J , CHEN P N ,et al. On the asymptotic performance of delay-constrained slotted ALOHA[C]// Proceedings of 2018 27th International Conference on Computer Communication and Networks (ICCCN). Piscataway,IEEE Press, 2018: 1-8.
[13]	ELSAWY H . Characterizing IoT networks with asynchronous time-sensitive periodic traffic[J]. IEEE Wireless Communications Letters, 2020,9(10): 1696-1700.
[14]	ZHAO L L , CHI X F , QIAN L ,et al. Analysis on latency-bounded reliability for adaptive grant-free access with multipackets reception (MPR)in URLLCs[J]. IEEE Communications Letters, 2019,23(5): 892-895.
[15]	JU H , ZHANG R . Throughput maximization in wireless powered communication networks[J]. IEEE Transactions on Wireless Communications, 2014,13(1): 418-428.
[16]	BIASON A , ZORZI M . Battery-powered devices in WPCNs[J]. IEEE Transactions on Communications, 2017,65(1): 216-229.
[17]	MICHELUSI N , ZORZI M . Optimal adaptive random multiaccess in energy harvesting wireless sensor networks[J]. IEEE Transactions on Communications, 2015,63(4): 1355-1372.
[18]	BIASON A , DEY S , ZORZI M . A decentralized optimization framework for energy harvesting devices[J]. IEEE Transactions on Mobile Computing, 2018,17(11): 2483-2496.
[19]	DIBANGOYE J S , AMATO C , BUFFET O ,et al. Optimally solving dec-POMDPs as continuous-state MDPs[J]. Journal of Artificial Intelligence Research, 2016,55: 443-497.
[20]	BAE Y H . Modeling timely-delivery ratio of slotted aloha with energy harvesting[J]. IEEE Communications Letters, 2017,21(8): 1823-1826.
[21]	BAE Y H , BAEK J W . Performance analysis of delay-constrained traffic in a cognitive radio network with RF energy harvesting[J]. IEEE Communications Letters, 2019,23(12): 2177-2181.
[22]	NIYATO D , WANG P . Delay-limited communications of mobile node with wireless energy harvesting,performance analysis and optimization[J]. IEEE Transactions on Vehicular Technology, 2014,63(4): 1870-1885.
[23]	JIA D Y , ZHU H H , ZOU S X ,et al. Dynamic cluster head selection method for wireless sensor network[J]. IEEE Sensors Journal, 2016,16(8): 2746-2754.
[24]	ULUKUS S , YENER A , ERKIP E ,et al. Energy harvesting wireless communications,a review of recent advances[J]. IEEE Journal on Selected Areas in Communications, 2015,33(3): 360-381.
[25]	SHAVIV D , ?ZGüR A , . Universally near-optimal online power control for energy harvesting nodes[J]. IEEE Journal on Selected Areas in Communications, 2016,34(12): 3620-3631.
[26]	BLASCO P , GUNDUZ D , DOHLER M . A learning theoretic approach to energy harvesting communication system optimization[J]. IEEE Transactions on Wireless Communications, 2013,12(4): 1872-1882.
[27]	WANG X , GONG J , HU C ,et al. Optimal power allocation on discrete energy harvesting model[J]. EURASIP Journal on Wireless Communications and Networking, 2015,2015(1): 1-14.
[28]	BAXTER L A . Markov decision processes,discrete stochastic dynamic programming[J]. Technometrics, 1995,37(3): 353.
[29]	DIBANGOYE J S , AMATO C , DONIEC A . Scaling up decentralized MDPs through heuristic search[C]// Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence. 2012: 217-226.
[30]	DIBANGOYE J S , AMATO C , DONIEC A ,et al. Producing efficient error-bounded solutions for transition independent decentralized MDPS[C]// AAMAS '13,Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems. 2013: 539-546.

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

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 30

相关文章 9

Metrics

推荐阅读 0

[1]	马柱华, 罗丽平. 非理想顺序干扰消除和信道状态信息下SWIPT-NOMA-CR网络中断性能[J]. 物联网学报, 2023, 7(1): 129-139.
[2]	俞汉清, 林艳, 贾林琼, 李强, 张一晋. 面向多目标救援的通信受限无人机集群分布式策略[J]. 物联网学报, 2022, 6(3): 103-112.
[3]	杜剑波, 薛哪哪, 孙艳, 姜静, 李树磊, 卢光跃. 基于NOMA的车辆边缘计算网络优化策略[J]. 物联网学报, 2021, 5(1): 19-26.
[4]	李亚平,熊轲,张煜,杨玺. 铁路物联网中无线携能中继网络性能分析[J]. 物联网学报, 2020, 4(4): 70-78.
[5]	马佳星,熊轲,张煜,钟章队,倪强. 无线能量收集驱动的铁路物联网中断性能分析[J]. 物联网学报, 2020, 4(3): 52-59.
[6]	李东博,贾敏,郭庆,顾学迈,刘晓锋. 物联网中双重非正交多址接入技术的性能分析[J]. 物联网学报, 2019, 3(1): 37-44.
[7]	乔冠华,冷甦鹏,刘浩,黄开胜,吴凡. 面向车辆多址接入边缘计算网络的任务协同计算迁移策略[J]. 物联网学报, 2019, 3(1): 51-59.
[8]	王璐瑶,张文倩,张光林. 多用户移动边缘计算迁移的能量管理研究[J]. 物联网学报, 2019, 3(1): 73-81.
[9]	王公仆, 熊轲, 刘铭, 高飞飞, 钟章队. 反向散射通信技术与物联网[J]. 物联网学报, 2017, 1(1): 67-75.