A Periodic Multinode Charging and Data Collection Scheme With Optimal Traveling Path in WRSNs

Lyu, Zengwei; Wei, Zhenchun; Wang, Xu; Fan, Yuqi; Xia, Chengkai; Shi, Lei

doi:10.1109/jsyst.2020.2977984

Cited by 37 publications

(21 citation statements)

References 24 publications

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“…Mo et al addressed the multiple Mobile Chargers (MCs) coordination problem under multiple requirements, which jointly optimized the scheduling, moving time and charging time of MCs [ 42 ]. Lyu et al, in [ 43 ], divided the network into multiple cells, and proposed a periodic multi-node charging and data collection scheme to maintain a perpetual operation. According to the importance of the sensor node, which was associated with the distance to the base station, Jiao et al in [ 44 ], divided sensor nodes into two types: Sensor nodes close to the base station and sensor nodes far away from the base station.…”

Section: Related Workmentioning

confidence: 99%

Hybrid Cyber Petri net Modelling, Simulation and Analysis of Master-Slave Charging for Wireless Rechargeable Sensor Networks

Qin

Zhao

et al. 2021

Sensors

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Wireless charging provides continuous energy for wireless sensor networks. However, it is difficult to replenish enough energy for all sensor nodes with fixed charging alone, and even more unrealistic to charge a large number of nodes within a short time via mobile charging. In order to overcome the above weaknesses, this paper firstly puts forward a Master-Slave Charging mode for the WRSN (Wireless Rechargeable Sensor Network), where fixed charging is the master mode and mobile charging is the slave mode, respectively. However, Master-Slave Charging is a typical hybrid system involving discrete event decision and continuous energy transfer. Therefore, the Hybrid Cyber Petri net system is proposed to build a visual specification with mathematical expression of Master-Slave Charging. Moreover, wireless charging in the WRSN is modeled and evaluated from the perspective of a hybrid system for the first time. Furthermore, a greedy-genetic algorithm is proposed to obtain the deployment of fixed chargers and the path planning of a mobile charger, by maximizing the actual electric quantity of the master charging problem and minimizing the mobile charger’s travelling path of the slave charging problem. Finally, the simulation results confirm and verify the Hybrid Cyber Petri net model for Master-Slave Charging. It is worth noting that the proposed model in this paper is highly adaptable to various charging modes in the WRSN.

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Section: Related Workmentioning

confidence: 99%

Hybrid Cyber Petri net Modelling, Simulation and Analysis of Master-Slave Charging for Wireless Rechargeable Sensor Networks

Qin

Zhao

et al. 2021

Sensors

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“…The distance between every two nodes of the inspection path is represented by d s n ,s n+1 . The total inspection path length is represented by d sum , which can be calculated by formula (3).…”

Section: System Modelmentioning

confidence: 99%

“…Intelligent manufacturing has emerged with the rapid development of information technology. IWSNs are one of the key technologies of intelligent manufacturing, and they are a combination of IWSNs and the Internet of Things [1][2][3]. Compared with traditional wired industrial sensor networks, it has the characteristics of fast deployment, high flexibility, and self-organization.…”

Section: Introductionmentioning

confidence: 99%

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An Adaptive Immune Ant Colony Optimization for Reducing Energy Consumption of Automatic Inspection Path Planning in Industrial Wireless Sensor Networks

Xiao

Liu

et al. 2021

Journal of Sensors

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Industrial wireless sensor networks (IWSNs) are usually fixedly deployed in industrial environments, and various sensor nodes cooperate with each other to complete industrial production tasks. The efficient work of each sensor node of IWSNs will improve the efficiency of the entire network. Automated robots need to perform timely inspection and maintenance of IWSNs in an industrial environment. Excessive inspection distance will increase inspection costs and increase energy consumption. Therefore, shortening the inspection distance can reduce production energy consumption, which is very important for the efficient operation of the entire system. However, the optimal detection path planning of IWSNs is an N-P problem, which can usually only be solved by heuristic mathematical methods. This paper proposes a new adaptive immune ant colony optimization (AIACO) for optimizing automated inspection path planning. Moreover, novel adaptive operator and immune operator are designed to prevent the algorithm from falling into the local optimum and increase the optimization ability. In order to verify the performance of the algorithm, the algorithm is compared with genetic algorithm (GA) and immune clone algorithm (ICA). The simulation results show that the inspection distance of IWSNs using AIACO is lower than that of GA and ICA. In addition, the convergence speed of AIACO is faster than that of GA and ICA. Therefore, the AIACO proposed in this paper can effectively reduce the inspection energy consumption of the entire IWSN system.

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“…Energy replenishment and data collection work at different frequencies; therefore, no interference exists. Many studies have developed mobile vehicle scheduling strategies to achieve efficient combinations of energy replenishment and data collection [ 22 , 23 , 24 , 25 , 26 ]. Corresponding results have indicated that the network performance could be improved significantly.…”

Section: Introductionmentioning

confidence: 99%

A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

Tian

Jiao

Chen

2021

Sensors

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In wireless rechargeable sensor networks, mobile vehicles (MVs) combining energy replenishment and data collection are studied extensively. To reduce data overflow, most recent work has utilized more vehicles to assist the MV to collect buffered data. However, the practical network environment and the limitations of the vehicle in the data collection are not considered. UAV-enabled data collection is immune to complex road environments in remote areas and has higher speed and less traveling cost, which can overcome the lack of the vehicle in data collection. In this paper, a novel framework joining the MV and UAV is proposed to prolong the network lifetime and reduce data overflow. The network lifetime is correlated with the charging order; therefore, we first propose a charging algorithm to find the optimal charging order. During the charging period of the MV, the charging time may be longer than the collecting time. An optimal selection strategy of neighboring clusters, which could send data to the MV, was found to reduce data overflow. Then, to further reduce data overflow, an algorithm is also proposed to schedule the UAV to assist the MV to collect buffered data. Finally, simulation results verified that the proposed algorithms can maximize network lifetime and minimize the data loss simultaneously.

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A Periodic Multinode Charging and Data Collection Scheme With Optimal Traveling Path in WRSNs

Cited by 37 publications

References 24 publications

Hybrid Cyber Petri net Modelling, Simulation and Analysis of Master-Slave Charging for Wireless Rechargeable Sensor Networks

Hybrid Cyber Petri net Modelling, Simulation and Analysis of Master-Slave Charging for Wireless Rechargeable Sensor Networks

An Adaptive Immune Ant Colony Optimization for Reducing Energy Consumption of Automatic Inspection Path Planning in Industrial Wireless Sensor Networks

A Joint Energy Replenishment and Data Collection Strategy in Heterogeneous Wireless Rechargeable Sensor Networks

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