GTCharge: A game theoretical collaborative charging scheme for wireless rechargeable sensor networks

Lin, Chi; Wu, Youkun; Liu, Zhicheng; Obaidat, Mohammad S.; Yu, Chang Wu; Wu, Guowei

doi:10.1016/j.jss.2016.08.046

Cited by 58 publications

(30 citation statements)

References 16 publications

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“…If there are nodes coming in and out, the base station will update its network topology structure. Dynamic TSP algorithm improves charging efficiency and reduces the path length, and the communication overhead is high . Madhja et al divided the network into several rectangles, each of which is taken care of by one WCV.…”

Section: Related Workmentioning

confidence: 99%

“…Dynamic TSP algorithm improves charging efficiency and reduces the path length, and the communication overhead is high. 10,39 Madhja et al 40 divided the network into several rectangles, each of which is taken care of by one WCV. In the initialization, each sensor node sends a message containing its ID and location to the responsible WCV, and the WCV will calculate a shortest loop to patrol the rectangle area.…”

Section: Related Workmentioning

confidence: 99%

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Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Wang

Lin

et al. 2020

Int J Communication

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Summary Prolonging network lifetime is a fundamental requirement in wireless sensor network (WSN). Existing charging scheduling algorithms suffer from high node redundancy and energy consumption issues. In this paper, we study WSN charging problem from the perspectives of energy conservation combined with energy replenishment scheduling. Firstly, we detect the redundant nodes whose energy is wasted in the network functionality and develop a K‐covering redundant nodes sleeping scheduling algorithm (KRSS) for reducing energy. Secondly, we employed multiple wireless charging vehicles (WCVs) for energy replenishment and optimize the charging scheduling algorithm to prevent any exhaustion of nodes, and we proposed a distance and energy–oriented charging scheduling algorithm (DECS) with multiple WCVs. Simulation experiments are conducted to show the advantages of the proposed KRSS+DECS, confirming that our scheme is capable of removing redundant nodes, lowering node failures, and prolonging network lifetime.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Wang

Lin

et al. 2020

Int J Communication

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“…In [12], the mobile charging mechanism for charging the sensor nodes is controlled with the model called Nearest First and Recent Rarest. A game theoretical collaborative charging scheme has been proposed in [13], in which the mobile charger involves in charging the weaker nodes as well as adding power to another mobile charger that is having less energy, but need to recharge many nodes. Further, a greedy algorithm based charging methodology has been developed in [14].…”

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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“…We developed a node capture attack algorithm that destroys the node with the maximum overlapping value. As GNRMK neglected analyzing destructiveness from the point of view of key sharing between nodes and paths, we used a matrix to express such relations ; we also took the energy cost into consideration when mounting an attack . However, MA still suffers from limitations; it pays little attention to the relationship between the attacking efficiency and the attacking cost.…”

Section: Related Workmentioning

confidence: 99%

“…However, the energy cost issue is neglected. In , we have proposed a graph‐based approach to model the effect of such an attack. Full graph attack (FGA) is designed to maximize destructiveness of the given network; however, it suffers from large computational and storage overhead.…”

Section: Introductionmentioning

confidence: 99%

MREA: a minimum resource expenditure node capture attack in wireless sensor networks

Lin

Qiu

Obaidat

et al. 2016

Security Comm Networks

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Because of the stochastic key pre‐distribution and complicated network topology, designing an energy‐efficient node capture attack algorithm is of great challenge. Although many algorithms have been proposed for node capture attack, previous methods lack of concerning minimizing resource expenditure in modeling attacking behavior. In this paper, we propose a novel way of modeling the node capture attack. First, we transform the problem into a set covering problem with a shortest Hamiltonian cycle problem, which has been shown to be NP‐hard. Consequently, we also develop a heuristic called minimum resource expenditure node capture attack (MREA) to maximize destructiveness while minimizing resource expenditure. Moreover, extensive simulations are conducted to show the performance of MREA. Simulation results show that MREA outperforms other algorithms in reducing the attack rounds and saving resource expenditure. Copyright © 2016 John Wiley & Sons, Ltd.

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GTCharge: A game theoretical collaborative charging scheme for wireless rechargeable sensor networks

Cited by 58 publications

References 16 publications

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

Prolonging lifetime for wireless rechargeable sensor networks through sleeping and charging scheduling

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

MREA: a minimum resource expenditure node capture attack in wireless sensor networks

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