You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger

Rao, Xunpeng; Yan, Yubo; Zhang, Maotian; Xu, Wanru; Fan, Xiaochen; Zhou, Hao; Yang, Panlong

doi:10.1109/access.2017.2741220

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…It can be seen from Table 3 that the obtained average value of the total charging cost is 328.7. Nine of the experimental results are higher than the average, the total cost of the optimal final solution is 304.8, the chromosome is [13,3,6,1,8,5,4,10,18,2,9,20,14,11,19,16,12,15,7,17]. As shown in Table 4, we can get its corresponding charging schedule path after the feasibility analysis.…”

Section: B Resultsmentioning

confidence: 99%

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Multi-MC Charging Schedule Algorithm With Time Windows in Wireless Rechargeable Sensor Networks

Wei

Zhao

et al. 2019

IEEE Access

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The limited lifespan of the traditional Wireless Sensor Networks (WSNs) has always restricted the broad application and development of WSNs. The current studies have shown that the wireless power transmission technology can effectively prolong the lifetime of WSNs. In most present studies on charging schedules, the sensor nodes will be charged once they have energy consumption, which will cause higher cost and lower networks utility. It is assumed in this paper that the sensor nodes in Wireless Rechargeable Sensor Networks (WRSNs) will be charged only after its energy is lower than a certain value. Each node has a charging time window and is charged within its respective time window. In large-scale wireless sensor networks, single mobile charger (MC) is difficult to ensure that all sensor nodes work properly. Therefore, it is propoesd in this paper that the multiple MCs which are used to replenish energy for the sensor nodes. When the average energy of all the sensor nodes falls below the upper energy threshold, each MC begins to charge the sensor nodes. The genetic algorithm has a great advantage in solving optimization problems. However, it could easily lead to inadequate search. Therefore, the genetic algorithm is improved by 2-opt strategy. And then multi-MC charging schedule algorithm with time windows based on genetic algorithm is proposed and simulated. The simulation results show that the algorithm designed in this paper can timely replenish energy for each sensor node and minimize the total charging cost.INDEX TERMS Wireless rechargeable sensor networks, charging schedule, time windows, multiple mobile chargers, energy threshold.

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Section: B Resultsmentioning

confidence: 99%

“…In recent years, many scholars have done a lot of researches on wireless energy transmission technology to prolong the lifetime of WRSNs [13]- [16]. Shi et al [17] studied the sensor networks based on the wireless energy transfer system for the first time.…”

Section: Related Workmentioning

confidence: 99%

Multi-MC Charging Schedule Algorithm With Time Windows in Wireless Rechargeable Sensor Networks

Wei

Zhao

et al. 2019

IEEE Access

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“…A look at a practicable way of maintaining the power duration and consequent power consumption of the deployed mobile sinks are also issues of great concern in this work. Rao et al [34], [35] in their works considered an optimal scheduling of mobile vehicles to travel along the shortest Hamiltonian cycle or path, hence eliminating an obvious trade-off of the resulting charging distances and angle between the mobile vehicle and the sensor nodes. Similarly, Jiang et al in [36] proposed the joint use of mobile charges (MCs) depot positioning technique, together with their respective charging tour planning, in order to solve or minimize the number of deployed MCs and to rapidly increase the rate of charging time over the total traveling time.…”

Section: Preliminaries and Related Workmentioning

confidence: 99%

Novel MA-VFBC Based Deployment of Obstacle-Avoiding Scattered Sensors for Region-of-Interest Incidence Monitoring

2020

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The deployment of mobile and adaptive virtual force barrier coverage (MA-VFBC) classification scheme using a mobile emergency response and command interface (MERCI) platform that is functionally implemented to track and report incidences and consequent collateral damages to infrastructures within a region of interest (ROI) is proposed. Considering the enormous use of the global positioning system (GPS) devices for location data-gathering and processing, and its inherent limitations, the proposed GUIbased MA-VFBC platform is implemented using self-deploying and obstacle-avoiding scattered mobile sensor nodes. The GPS service is kept as alternatives, since only initial coordinates from where the deployed sensor starts to move and the maximum boundary location of the target location is considered. The practical experimentation work appraises the use and feel of the (MERCI) platform when integrated with the proposed novel MA-VFBC path-tracking classification schemes, while the simulation work investigates evident real-time system reliability issues as direction of node deployment with path distances, system computation time and system overheads in the presence of dissimilar multiple obstacles. INDEX TERMS Emergency response, mobile and adaptive virtual force barrier coverage (MA-VFBC), MERCI, obstacle-avoiding sensor nodes, ROI incidence assessment.

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“…Due to the different functions and performance of different sensors, the energy consumption speed of these batteries is different. Therefore, for large-scale WRSNs, the on-demand charging scheme is better than the regular energy replenishment scheme (Lin, C., Han, D., Deng, J., & Wu, G., 2017;Rao et al, 2018;Tomar, A., Muduli, L., & Jana, P. K., 2019).…”

Section: Introductionmentioning

confidence: 99%

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

Chen

2023

International Journal of Grid and High Performance Computing

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Wireless rechargeable sensor networks (WRSNs) have received a lot of attention due to the development of wireless charging technology. Recently, a new solution of wireless charging vehicle (WCV) for WRSNs with separable charger array equipped with multiple chargers was suggested. By this method, each charger can be unloaded to serve one sensor, while the WCV can work in a very efficient way because it needs not to stay on site and can continue to perform its assigned task. But this solution created a new problem that is how to recollect these chargers for reusing when their charging services are finished. In previous research, however, the recollecting strategy has seldom been considered. In this work, an effectively opportunistic charger recollection algorithm (OCRA) are proposed. Simulation results indicate that OCRA has outperformed previous algorithms in many aspects.

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You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger

Cited by 9 publications

References 31 publications

Multi-MC Charging Schedule Algorithm With Time Windows in Wireless Rechargeable Sensor Networks

Multi-MC Charging Schedule Algorithm With Time Windows in Wireless Rechargeable Sensor Networks

Novel MA-VFBC Based Deployment of Obstacle-Avoiding Scattered Sensors for Region-of-Interest Incidence Monitoring

An Opportunistic Charger Recollection Algorithm for Wireless Rechargeable Sensor Networks

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