一种按需多节点优先级充电调度算法

doi:10.16180/j.cnki.issn1007-7820.2021.08.008

摘要/Abstract

摘要：

无线可充电传感器网络中,大部分现有的移动充电调度方案集中在周期性充电方案和单节点充电模型。但周期性充电忽略了网络的动态变化因素,通常导致充电性能较低。单节点充电模型的充电效率低,可扩展性差。针对这一问题,文中基于多节点充电模型,提出了一种按需多节点优先级调度算法,旨在减少死亡节点个数以及能量消耗。同时,文中对传感器的能量消耗模型提出了一种新的与基站距离有关的线性模型。在节点分组时,为了减少停止点的数量并平衡节点的充电时间,开发了一种基于形心的聚类算法。在路径规划时,综合考虑了节点的剩余寿命以及停止点与移动充电器之间的距离因素。最后,通过实验证明了所提算法可以有效地减少节点死亡和能量消耗。

关键词: 无线可充电传感器网络, 充电调度, 多节点充电模型, 按需充电, 优先级, 移动充电器, 停止点, 路径规划

Abstract:

Most of the existing mobile charging scheduling schemes in wireless rechargeable sensor networks focus on periodic charging schemes and single-node charging models, but periodic charging ignores the dynamic changes of the network and often results in low charging performance, and the single-node charging model has low charging efficiency and poor scalability. In view of this problem, based on the multi-node charging model, an on-demand multi-node priority scheduling algorithm is proposed to reduce the number of dead nodes and energy consumption in this study. At the same time, a new linear model related to the distance of the base station is proposed for the energy consumption model of the sensor. In grouping nodes, in order to reduce the number of stopping points and balance the charging time of the nodes, a centroid-based clustering algorithm is developed. In the path planning, the remaining life of the node and the distance between the stopping point and the mobile charger are also considered. Finally, experiments verify that the proposed algorithm can effectively reduce node death and energy consumption.

Key words: wireless rechargeable sensor networks, charging schedule, multi-node charging model, on-demand charging, priority, mobile charger, stopping point, path planning

中图分类号:

TP393

水九生,王然. 一种按需多节点优先级充电调度算法[J]. 电子科技, 2021, 34(8): 43-49.

SHUI Jiusheng,WANG Ran. A On-Demand Multi-Node Priority Charging Scheduling Algorithm[J]. Electronic Science and Technology, 2021, 34(8): 43-49.

图/表 11

图1

图2

图3

图4

图5

图6

表1

图7

图8

图9

图10

参考文献 16

[1]	Rahimi M, Shah H, Sukhatme G S, et al. Studying the feasibility of energy harvesting in a mobile sensor network[C]. Taipei:IEEE International Conference on Robotics and Automation, 2003.
[2]	Kausar A S M Z, Reza A W, Saleh M U, et al. Energizing wireless sensor networks by energy harvesting systems: Scopes, challenges and approaches[J]. Renewable and Sustainable Energy Reviews, 2014,38(5):973-989.
[3]	Kurs A, Karalis A, Moffatt R, et al. Wireless power transfer via strongly coupled magnetic resonances[J]. Science, 2007,317(5834):83-86.
[4]	Fu L K, Cheng P, Gu Y, et al. Minimizing charging delay in wireless rechargeable sensor networks[C]. Turin: Proceedings IEEE INFOCOM, 2013.
[5]	Dai H P, Wu X B, Xu L J, et al. Using minimum mobile chargers to keep large-scale wireless rechargeable sensor networks running forever[C]. Nassau:The Twenty-second International Conference on Computer Communication and Networks, 2013.
[6]	Fu L K, Cheng P, Gu Y, et al. Optimal charging in wireless rechargeable sensor networks[J]. IEEE Transactions on Vehicular Technology, 2016,65(1):278-291.
[7]	Shi Y, Xie L G, Hou Y T, et al. On renewable sensor networks with wireless energy transfer[C]. Shanghai: Proceedings IEEE INFOCOM, 2011.
[8]	Xie L G, Shi Y, Hou Y T, et al. Multi-node wireless energy charging in sensor networks[J]. IEEE/ACM Transactions on Networking, 2014,23(2):437-450.
[9]	马辉, 王然, 程宗毛. 基于中继充电模型的充电小车休息时间最大化方法[J]. 电子科技, 2019,33(7):31-36.
	Ma Hui, Wang Ran, Cheng Zongmao. A method for maximizing the rest time of charging trolley based on relay charging model[J]. Electronic Science and Technology, 2019,33(7):31-36.
[10]	Jiang L T, Wu X B, Chen G H, et al. Effective on-demand mobile charger scheduling for maximizing coverage in wireless rechargeable sensor networks[J]. Mobile Networks and Applications, 2014,19(4):543-551.
[11]	He L, Kong L H, Gu Y, et al. Evaluating the on-demand mobile charging in wireless sensor networks[J]. IEEE Transactions on Mobile Computing, 2015,14(9):1861-1875.
[12]	Lin C, Wang Z Y, Han D, et al. TADP: Enabling temporal and distantial priority scheduling for on-demand charging architecture in wireless rechargeable sensor networks[J]. Journal of Systems Architecture, 2016,70(2):26-38.
[13]	Khelladi L, Djenouri D, Rossi M, et al. Efficient on-demand multi-node charging techniques for wireless sensor networks[J]. Computer Communications, 2017,101(3):44-56.
[14]	Lin C, Han D, Deng J, et al. P²S:A primary and passer-by scheduling algorithm for on-demand charging architecture in wireless rechargeable sensor networks[J]. IEEE Transactions on Vehicular Technology, 2017,66(9):8047-8058.
[15]	Kurs A, Moffatt R, Soljaĉiĉ M. Simultaneous mid-range power transfer to multiple devices[J]. Applied Physics Letters, 2010,96(4):044102-1-3.
[16]	Wu G W, Lin C, Li Y, et al. A multi-node renewable algorithm based on charging range in large-scale wireless sensor network[C]. Blumenau:The Ninth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, 2015.

参数	数值
网络规模/m²	100×100
传感器电池容量/J	50
传感器能量消耗率/J·s^-1	[0.01,0.06]
充电请求阈值L_r	0.3
充电启动阈值L_c	0.2
能量效率传递η(d)	-0.095 8d²-0.037 7d+1.0
MC的行驶速度/m·s^-1	2
MC的充电功率/W	5
MC的行驶功率/J·m^-1	15
MC的充电半径/m	2.7