Energy Provisioning in Wireless Rechargeable Sensor Networks

He, Shibo; Chen, Jiming; Jiang, Fachang; Yau, David K. Y.; Xing, Guoliang; Sun, Youxian

doi:10.1109/tmc.2012.161

Cited by 558 publications

(102 citation statements)

References 22 publications

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“…In this section, we review the research results [3][4][5][6][7][8][13][14][15][16][17] most related to our work. Kim et al [3] investigated various ambient energy-harvesting technologies using different power sources, such Energies 2016, 9, 696 3 of 22 as solar power, thermal power, piezoelectric power, and wireless RF power, in the aspect of their applicability for self-sustainable wireless sensor platforms.…”

Section: Related Workmentioning

confidence: 99%

“…He et al [5] proposed two types of energy provisioning problems for WRSNs: point provisioning and path provisioning. The former addresses how to use the least number of chargers to ensure that a static sensor node placed in any position of the network will receive a sufficient recharge rate to ensure WRSN sustainability.…”

Section: Related Workmentioning

confidence: 99%

“…The replenishing is achieved by equipping every sensor node with an energy harvester to harvest energy from different sources [2,3], such as solar power, thermal power, radio frequency (RF) waves, or air flow, as shown in Figure 1. Many recent studies [4][5][6][7][8][9][10][11][12][13] focus on the WRSNs due to their sustainability. Some other studies [14][15][16][17][18][19][20] investigate battery-less or battery-free wireless sensor networks (WSNs) in which sensor nodes are powered by capacitors storing energy harvested through wireless power transmission (WPT), especially microwave power transmission (MPT).…”

Section: Introductionmentioning

confidence: 99%

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Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Jiang

Liao

2016

Energies

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A wireless rechargeable sensor network (WRSN) consists of sensor nodes that can harvest energy emitted from wireless chargers for refilling their batteries so that the WRSN can operate sustainably. This paper assumes wireless chargers are equipped with directional antennas, and are deployed on grid points of a fixed height to propose two heuristic algorithms solving the following wireless charger deployment optimization (WCDO) problem: how to deploy as few as possible chargers to make the WRSN sustainable. Both algorithms model the charging space of chargers as a cone and calculate charging efficiency according power regression expressions complying with the Friis transmission equation. The two algorithms are the greedy cone covering (GCC) algorithm and the adaptive cone covering (ACC) algorithm. The GCC (respectively, ACC) algorithm greedily (respectively, adaptively) generates candidate cones to cover as many as possible sensor nodes. Both algorithms then greedily select the fewest number of candidate cones, each of which corresponds to the deployment of a charger, to have approximate solutions to the WCDO problem. We perform experiments, conduct simulations and do analyses for the algorithms to compare them in terms of the time complexity, the number of chargers deployed, and the execution time.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Jiang

Liao

2016

Energies

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“…We adopt the following charging model of the WISP reader proposed and experimentally verified in [13] …”

Section: Wireless Charging Modelmentioning

confidence: 99%

Achieving Collision-Free Communication by Time of Charge in WRSN

Tian

Cheng

et al. 2015

Mobile Netw Appl

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The Wireless Identification and Sensing Platform (WISP) Sample et al. (IEEE T Instrum Meas 57(11):2608-2615 has become a very promising experimental platform of wireless rechargeable sensor networks (WRSN), which integrates the sensing and computation capabilities to the traditional RFID tags. In such kind of networks, the simultaneous transmission may introduce severe communication collisions, which have attracted various research efforts for resolving such collisions at the MAC layer. However, different from existing works, we avoid such communication collisions through proper reader movement by exploiting the differences in the time of charge among rechargeable sensor nodes. We formulate the optimization problem and prove that complexity of the optimal solution is NP-hard, and propose a simple yet effective algorithm to optimize both the reader stop location and stop time for minimizing the total communication delay. Extensive simulations under different system settings show that our design can largely reduce the communication delay and outperform the baseline design by at least 20 %.

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“…We review a number of the relevant previous studies. He et al [10] focused on the omnidirectional wireless charger deployment problem and deployed charging devices in the sensing area of interest to provide enough charging power to maintain the operation of the network, but they explored the space with a more traditional triangle solution. Chiu et al [11] divided the sensing areas into grids and placed omnidirectional wireless chargers on various grid points.…”

Section: Introductionmentioning

confidence: 99%

A Power Balance Aware Wireless Charger Deployment Method for Complete Coverage in Wireless Rechargeable Sensor Networks

Lin

Chang

2016

Energies

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Abstract:Traditional sensor nodes are usually battery powered, and the limited battery power constrains the overall lifespan of the sensors. Recently, wireless power transmission technology has been applied in wireless sensor networks (WSNs) to transmit wireless power from the chargers to the sensor nodes and solve the limited battery power problem. The combination of wireless sensors and wireless chargers forms a new type of network called wireless rechargeable sensor networks (WRSNs). In this research, we focus on how to effectively deploy chargers to maximize the lifespan of a network. In WSNs, the sensor nodes near the sink consume more power than nodes far away from the sink because of frequent data forwarding. This important power unbalanced factor has not been considered, however, in previous charger deployment research. In this research, a power balance aware deployment (PBAD) method is proposed to address the power unbalance in WRSNs and to design the charger deployment with maximum charging efficiency. The proposed deployment method is effectively aware of the existence of the sink node that would cause unbalanced power consumption in WRSNs. The simulation results show that the proposed PBAD algorithm performs better than other deployment methods, and fewer chargers are deployed as a result.

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Energy Provisioning in Wireless Rechargeable Sensor Networks

Cited by 558 publications

References 22 publications

Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Efficient Wireless Charger Deployment for Wireless Rechargeable Sensor Networks

Achieving Collision-Free Communication by Time of Charge in WRSN

A Power Balance Aware Wireless Charger Deployment Method for Complete Coverage in Wireless Rechargeable Sensor Networks

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