Charging Wireless Rechargeable Sensor Networks Deployed in a Rectangular Street Grid

Myung, Sunghee; Lee, Sangkeum; Moraes, Celso; Har, Dongsoo

doi:10.1109/apwc-on-cse.2016.034

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…To enhance the overall lifetime of the network, the scheduling of the WCV is designed to charge specific sensor nodes partially, as discussed by Zhu et al [21]. Myung et al [22] examined the charging technique for the wireless sensor network implemented in a rectangular route grid whereas Rao et al [23] suggested optimal charging techniques that aim to minimize the time required for recharging. These strategies take into account both the charging distance and the angle between the sensor nodes and the WCV simultaneously.…”

Section: Preliminariesmentioning

confidence: 99%

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Mukase,

Xia,

Owoola

2024

Preprint

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Recently, the research community has shown a growing interest in using mobile chargers to recharge the energy supply of sensor nodes in wireless rechargeable sensor network (WRSN). Mobile energy chargers offer a more dependable energy source compared to devices that harvest dynamic energy from the surrounding environment. This research introduces a synthetic on-demand charging optimization approach using Adaptive Crossover Mayfly Algorithm (ADCMA) to enhance the charging performance in WRSN. The genetic operator of roulette wheel selection is employed to choose possibly valuable solutions for crossover and the objective is to reduce the overall energy consumption of the system and the mobile charger's total distance traveled, while simultaneously enhancing its vacation time ratio. Unlike prior systems that required the mobile charger to visit and charge all nodes in every cycle, this strategy simply requires the mobile charger to visit a subset of nodes. The proposed ADCMA is also tested on 46 benchmark functions and applied to the on-demand charging model by comparing it with other well-known seven algorithms. The mathematical results demonstrate that the ADCMA effectively decreases the overall energy consumption and distance traveled by the mobile charging device, while still maintaining performance. This algorithm is particularly advantageous for real-world networks as it allows for the network to remain operational with reduced complexity compared to other approaches.

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Section: Preliminariesmentioning

confidence: 99%

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Mukase,

Xia,

Owoola

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…By scheduling the WCV to charge partial sensor nodes, the lifetime of the whole network is maximized in [13]. Authors in [14] investigated the charging method for the wireless sensor network deployed in a rectangular street grid. In [15], authors proposed optimal charging strategies to minimize the recharging cycle time considering the charging distance and the angle between sensor nodes and the WCV simultaneously.…”

Section: Introductionmentioning

confidence: 99%

The Charging Strategy of Mobile Charging Vehicles in Wireless Rechargeable Sensor Networks With Heterogeneous Sensors

2020

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Energy shortage obstructs the applications of the wireless rechargeable sensor network (WRSN). With the development of the wireless energy transfer technology, the mobile wireless charging vehicle (WCV) becomes a promising solution to solve that problem. However, the importance of different sensor nodes in the data transmission and uneven energy consumptions are often ignored. In this paper, the charging strategy of the WCV is studied in the WRSN considering these two phenomena. According to the importance of the sensor node, which is associated with the distance to the base station, we divide sensor nodes into two types: sensor nodes in ring 0 and sensor nodes in outer ring. We propose a novel charging model, the WCV adopts different charging strategies for different sensor nodes. To make the charging more efficient, the WCV charges sensor nodes one by one in ring 0 first, and then charges multiple sensor nodes simultaneously in outer ring. To estimate the lifetime of the network, a new metric named as the normalized dead time is proposed. Maximizing the lifetime of the network is modeled as minimizing the sum normalized dead time, and an efficient algorithm is proposed to minimize the sum normalized dead time through searching the optimal charging timeslots sequences. Then, through reassigning charging timeslots of sensor nodes, the proposed minimum travel cost algorithm minimizes the travel distance of the WCV and guarantee the lifetime of the network. We further deploy a cluster head node which has larger battery capacity in each cluster and can charge other sensor nodes within a limited distance. An algorithm is proposed to pre-distribute energy of the cluster head node. At last, the performance of proposed algorithms is verified by MATLAB. The results indicate that the performance of the WRSN can be improved by our proposed algorithms. INDEX TERMS Wireless rechargeable sensor network, wireless energy transfer technology, mobile wireless charging vehicle, charging strategy, sum normalized dead time minimization, travel cost minimization.

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Proposal Specifications of Building Data Centre for Virtual GlobalNets

Al-Sabaawi

Ibrahim

Almalullah

et al. 2019

2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)

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Charging Wireless Rechargeable Sensor Networks Deployed in a Rectangular Street Grid

Cited by 3 publications

References 7 publications

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

Synthetic on-demand charging optimization with ADCMA for energy conservation in WRSN

The Charging Strategy of Mobile Charging Vehicles in Wireless Rechargeable Sensor Networks With Heterogeneous Sensors

Proposal Specifications of Building Data Centre for Virtual GlobalNets

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