基于中继多跳模型的传感网络充电方法研究

doi:10.16180/j.cnki.issn1007-7820.2021.08.006

Abstract

Abstract:

Under the condition of ensuring that the wireless rechargeable network can last for a long time, based on the relay multi-hop charging model, the problem of maximizing the energy utilization of the charging car in the sensor network is studied. To solve this problem, a relay node selection algorithm and path planning algorithm is proposed. The relay node selection algorithm is used to select relay nodes from sensor nodes and serves as a stop for charging cars, and uses the number of nodes covered by the relay as the basis for selection. The path planning algorithm is based on Hamiltonian loop re-optimization to plan the moving path for the charging car. By using the relay multi-hop charging model and the above algorithm, the charging car can reduce the loss of mobile energy, thereby improving energy utilization. Through simulation experiments, the two strategies of NJNP and TADP and the effects of different scale networks are compared. The results show that the proposed scheme can improve energy utilization by 15%~25%, and has good performance in large-scale sensor networks.

Key words: wireless rechargeable sensor network, wireless charging car, relay charging, charging scheduling planning, multi-hop charging, on-demand charging, path planning, energy utilization

CLC Number:

TP393

YE Hengchao,CHENG Zongmao. Research on Charging Method of Sensor Network Based on Relay Multi-Hop Model[J].Electronic Science and Technology, 2021, 34(8): 31-36.

Figures/Tables 6

Table 1

Symbol description"

符号	含义
E_i	节点i接收到的充电能量
l_ij	节点i和j之间的距离
c_i	节点i的能量消耗速率
μ_l	两节点距离为l时所对应的充电效率
E₀	充电小车充电的输出能量
v_i	充电小车移动每单位的耗电量
η	充电小车能量利用率
E_node	传感器节点电池电量
E_car	充电小车电池电量
$Q current (j)$	当前中继范围内节点的个数

Table 1

Figure 1.

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Figure 3.

Figure 4.

Figure 5.

References 17

[1]	Lin C, Zhou J, Guo C, et al. TSCA:A temporal-spatial real-time charging scheduling algorithm for on-demand architecture in wireless rechargeable sensor networks[J]. IEEE Transactions on Mobile Computing, 2017,17(1):211-224.
[2]	He L, Gu Y, Pan J, et al. On-demand charging in wireless sensor networks: Theories and applications[C]. Hangzhou:IEEE the Tenth International Conference on Mobile Ad-Hoc and Sensor Systems, 2013.
[3]	Liang W, Xu Z, Xu W, et al. Approximation algorithms for charging reward maximization in rechargeable sensor networks via a mobile charger[J]. IEEE/ACM Transactions on Networking, 2017,25(5):3161-3174.
[4]	Ma Y, Liang W, Xu W. Charging utility maximization in wireless rechargeable sensor networks by charging multiple sensors simultaneously[J]. IEEE/ACM Transactions on Networking, 2018,26(4):1591-1604.
[5]	Lin C, Xue B, Wang Z, et al. DWDP:A double warning thresholds with double preemptive scheduling scheme for wireless rechargeable sensor networks[C]. New York: IEEE the Seventeenth International Conference on High Performance Computing and Communications,IEEE the Seventeenth International Symposium on Cyberspace Safety and Security,IEEE the Twelfth International Conference on Embedded Software and Systems, 2015.
[6]	Lin C, Wang Z, 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(6):26-38.
[7]	Lin C, Han D, Deng J, et al. 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.
[8]	Lin C, Zhou Y, Song H, et al. OPPC:An optimal path planning charging scheme based on schedulability evaluation for wrsns[J]. ACM Transactions on Embedded Computing Systems, 2017,17(1):1-25.
[9]	Qin Z, Zhou C, Yu Y, et al. A practical solution to wireless energy transfer in WSNs[C]. Jeju:International Conference on ICT Convergence, 2013.
[10]	Liang W, Xu W, Ren X, et al. Maintaining sensor networks perpetually via wireless recharging mobile vehicles[C]. Edmonton:The Thirty-ninth Annual IEEE Conference on Local Computer Networks, 2014.
[11]	He L, Kong L, Gu Y, et al. Evaluating the on-demand mobile charging in wireless sensor networks[J]. IEEE Transactions on Mobile Computing, 2014,14(9):1861-1875.
[12]	Peng Y, Li Z, Zhang W, et al. Prolonging sensor network lifetime through wireless charging[C]. San Diego:The Thirty-first IEEE Real-Time Systems Symposium, 2010.
[13]	Zhang S, Qian Z, Kong F, et al. P3:Joint optimization of charger placement and power allocation for wireless power transfer[C]. San Diego:IEEE Conference on Computer Communications, 2015.
[14]	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.
[15]	Khelladi L, Djenouri D, Lasla N, et al. Msr: minimum-stop recharging scheme for wireless rechargeable sensor networks[C]. Bali:IEEE the Eleventh Intl Conference on Ubiquitous Intelligence and Computing,IEEE the Eleventh Intl Conference on Autonomic and Trusted Computing,IEEE the Fourteenth International Conference on Scalable Computing and Communications and Its Associated Workshops, 2014.
[16]	Wang C, Li J, Ye F, et al. A novel framework of multi-hop wireless charging for sensor networks using resonant repeaters[J]. IEEE Transactions on Mobile Computing, 2016,16(3):617-633.
[17]	谭杜坤. 一种基于信道-网络编码的双中继传输方案[J]. 电子设计工程, 2016,24(13):110-112.
	Tan Dukun. Scherne of double relay transmission based on network-chamel cading[J]. Electronic Design Eigineering, 2016,24(13):110-112.

Research on Charging Method of Sensor Network Based on Relay Multi-Hop Model

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