Joint Charging Tour Planning and Depot Positioning for Wireless Sensor Networks Using Mobile Chargers

Jiang, Guiyuan; Lam, Siew-Kei; Sun, Yuqing; Tu, Lijia; Wu, Jigang

doi:10.1109/tnet.2017.2684159

Cited by 87 publications

(36 citation statements)

References 44 publications

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“…The MC energy is limited in [12]- [16]. The authors in [12] jointly optimize the BS positioning and the MC scheduling. They maximize the charging efficiency, while reducing the number of required MCs and BSs.…”

Section: A Related Workmentioning

confidence: 99%

“…Therefore, the number of available MCs is time-varying, which influences the scheduling, the moving time and the charging time of the MCs. Moreover, the charging optimization problems usually aim to enhance the charging efficiency [8], [12], [13], [18] or reduce the energy consumption of the MCs [1], [7], [9]. Therefore, the problem becomes more realistic, when the constraints related to the limited MC energy budget are taken into account.…”

Section: Introductionmentioning

confidence: 99%

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Energy-Aware Multiple Mobile Chargers Coordination for Wireless Rechargeable Sensor Networks

Kritikakou

2019

IEEE Internet Things J.

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Wireless charging provides dynamic power supply for Wireless Sensor Networks (WSNs). Such systems, are typically considered under the scenario of Wireless Rechargeable Sensor Networks (WRSNs). With the use of mobile chargers (MCs), the flexibility of WRSNs is further enhanced. However, the use of MCs poses several challenges during the system design. The coordination process has to simultaneously optimize the scheduling, the moving time and the charging time of multiple MCs under limited system resources (time and energy). Efficient methods that jointly solve these challenges are generally lacking in the literature. In this paper, we address the multiple MCs coordination problem under multiple system requirements. Firstly, we aim at minimizing the energy consumption of MCs, guaranteeing that every sensor will not run out of energy. We formulate the multiple MCs coordination problem as a mixed-integer linear programming and derive a set of desired network properties. Secondly, we propose a novel decomposition method to optimally solve the problem, as well as to reduce the computation time. Our approach divides the problem into a subproblem for the MC scheduling and a subproblem for the MC moving time and charging time, and solves them iteratively by utilizing the solution of one into the other. The convergence of proposed method is analyzed theoretically. Simulation results demonstrate the effectiveness and scalability of the proposed method in terms of solution quality and computation time.

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Section: A Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy-Aware Multiple Mobile Chargers Coordination for Wireless Rechargeable Sensor Networks

Kritikakou

2019

IEEE Internet Things J.

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“…For replenishing the power from the mobile charger for the maximum possible sensor nodes, an efficient charging route is required. In the work [19], the factors such as utmost energy capacity of mobile charger and the residual energy of sensor nodes are considered for estimating, whether the mobile recharger accomplishes the desired tack and back to the BS before depleted its complete energy.…”

Section: Related Workmentioning

confidence: 99%

Schedule-based Optimized Node Recharging Model (SONRM) For Increasing Longevity of Wireless Rechargeable Sensor Network (WRSN)

Sakthidharan¹,

Reddy²

2019

IJIES

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There has been a tremendous growth in research concern in Wireless Sensor Networks (WSNs), due to the broad range of applications in distinctive areas such as environmental observation, security domains, home automation, etc. Despite advantages, the prevalent adoption of WSN, specifically in remote and isolated regions, has become the major challenge, because of this battery constrained network with limited energy source. As advancement, the nodes are framed under Wireless Rechargeable Sensor Network (WRSN) to enhance the lifetime of sensor nodes with the establishment of charging mechanisms. With those considerations, this paper presents a Schedule-based Optimized Node Recharging Model (SONRM), in accordance to the condition of limited capability of mobile charging. In the process of the construction of charging circuit, the SONRM effectively considers the dynamic changes of energy utilization among nodes at different factors and develops a Recharge Scheduling Algorithm (RSA) that helps in finding the next Energy Starving Sensor Node (ESSN) to be recharged. Simultaneously, a model for the establishment of feasible circuit for recharging has also been done for ensuring the effectiveness of charging. During the operation, the node mortality can be reduced by the proposed model with the incorporation of dynamic charging threshold. When compared with the existing mechanisms, the SONRM attains better results on analysing decisive factors such as network longevity, service time, efficient charging, throughput and recharging time.Keywords: Wireless rechargeable sensor network (WRSN), Schedule-based optimized node recharging model (SONRM), Recharge scheduling algorithm (RSA), Energy starving sensor node (ESSN).

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“…The employment of mobile charging vehicles is a promising technique to replenish sensor energy, and the vehicle scheduling for prolonging network lifetimes has been studied in literature. Most of these studies assumed that every sensor is powered with a low-cost off-the-shelf battery [ 17 , 18 , 19 , 20 , 21 , 23 , 38 , 39 , 40 ], e.g., Lithium battery, where the price of such a battery is about only a few dollars [ 31 ]. It, however, usually takes some non-trivial time to fully charge such a battery, e.g., 30–80 min [ 26 ].…”

Section: Related Workmentioning

confidence: 99%

“…On the other hand, some other studies [ 21 , 38 , 39 , 40 ] employed multiple charging vehicles to maintain sensor networks perpetually. Liang et al [ 40 ] devised an approximation algorithm to minimize the number of dispatched vehicles to charge energy-critical sensors, subject to the energy capacity of each vehicle.…”

Section: Related Workmentioning

confidence: 99%

Towards Low-Cost Yet High-Performance Sensor Networks by Deploying a Few Ultra-fast Charging Battery Powered Sensors

Guo

et al. 2018

Sensors

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The employment of mobile vehicles to charge sensors via wireless energy transfer is a promising technology to maintain the perpetual operation of wireless sensor networks (WSNs). Most existing studies assumed that sensors are powered with off-the-shelf batteries, e.g., Lithium batteries, which are cheap, but it takes some non-trivial time to fully charge such a battery (e.g., 30–80 min). The long charging time may incur long sensor dead durations, especially when there are many lifetime-critical sensors to be charged. On the other hand, other studies assumed that every sensor is powered with an ultra-fast charging battery, where it only takes some trivial time to replenish such a battery, e.g., 1 min, but the adoption of many ultra-fast sensors will bring about high purchasing cost. In this paper, we propose a novel heterogeneous sensor network model, in which there are only a few ultra-fast sensors and many low-cost off-the-shelf sensors. The deployment cost of the network in the model is low, as the number of ultra-fast sensors is limited. We also have an important observation that we can significantly shorten sensor dead durations by enabling the ultra-fast sensors to relay more data for lifetime-critical off-the-shelf sensors. We then propose a joint charging scheduling and routing allocation algorithm, such that the longest sensor dead duration is minimized. We finally evaluate the performance of the proposed algorithm through extensive simulation experiments. Experimental results show that the proposed algorithm is very promising and the longest sensor dead duration by it is only about 10% of those by existing algorithms.

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Joint Charging Tour Planning and Depot Positioning for Wireless Sensor Networks Using Mobile Chargers

Cited by 87 publications

References 44 publications

Energy-Aware Multiple Mobile Chargers Coordination for Wireless Rechargeable Sensor Networks

Energy-Aware Multiple Mobile Chargers Coordination for Wireless Rechargeable Sensor Networks

Schedule-based Optimized Node Recharging Model (SONRM) For Increasing Longevity of Wireless Rechargeable Sensor Network (WRSN)

Towards Low-Cost Yet High-Performance Sensor Networks by Deploying a Few Ultra-fast Charging Battery Powered Sensors

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