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CCSO: a dynamic collaborative scheduling scheme for wireless rechargeable sensor networks with obstacles.

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Title: CCSO: a dynamic collaborative scheduling scheme for wireless rechargeable sensor networks with obstacles.
Authors: Zeng, Gang1 (AUTHOR), Wang, Kun1 (AUTHOR) wangkunmuwewen007@gmail.com
Source: Wireless Networks (10220038). Aug2024, Vol. 30 Issue 6, p6161-6176. 16p.
Subjects: Fresnel diffraction, Dynamic loads, Wireless sensor networks, Job performance, Scheduling, Detectors
Abstract: In this paper, we focus on the dynamic collaborative charging scheduling problem with multiple Mobile Chargers (MCs) in the Wireless Rechargeable Sensor Networks (WRSNs) with obstacles. Firstly, we use the Fresnel Diffraction Model (FDM) to describe the influences of obstacles on the charging process. Secondly, we propose a new charging group division algorithm, which can select the sets of the sensor nodes that can be charged simultaneously and determine the selection ranges of the charging spots. Thirdly, we propose a charging spots selection algorithm based on the FDM, which can not only reduce the number of sensor failures, but also guarantee the high-level charging utility. Fourthly, we propose a dynamic zonal collaborative charging scheduling scheme. It divides the charging zones to achieve balanced distribution of the charging loads. When a zone is not schedulable, our scheme will redistribute its high energy-cost charging tasks to the zone with less load for dynamic adjustment. When some charging tasks can not be adjusted, our scheme will discard the ones with less contribution, minimizing the losses of the network. Finally, we conduct a large number of simulations to verify the performances of our work. The simulation results show that our scheme has obviously better performances compared with the other arts. [ABSTRACT FROM AUTHOR]
Copyright of Wireless Networks (10220038) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: CCSO: a dynamic collaborative scheduling scheme for wireless rechargeable sensor networks with obstacles.
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  Data: <searchLink fieldCode="AR" term="%22Zeng%2C+Gang%22">Zeng, Gang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Kun%22">Wang, Kun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wangkunmuwewen007@gmail.com</i>
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  Data: <searchLink fieldCode="JN" term="%22Wireless+Networks+%2810220038%29%22">Wireless Networks (10220038)</searchLink>. Aug2024, Vol. 30 Issue 6, p6161-6176. 16p.
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  Data: <searchLink fieldCode="DE" term="%22Fresnel+diffraction%22">Fresnel diffraction</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+loads%22">Dynamic loads</searchLink><br /><searchLink fieldCode="DE" term="%22Wireless+sensor+networks%22">Wireless sensor networks</searchLink><br /><searchLink fieldCode="DE" term="%22Job+performance%22">Job performance</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Detectors%22">Detectors</searchLink>
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  Label: Abstract
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  Data: In this paper, we focus on the dynamic collaborative charging scheduling problem with multiple Mobile Chargers (MCs) in the Wireless Rechargeable Sensor Networks (WRSNs) with obstacles. Firstly, we use the Fresnel Diffraction Model (FDM) to describe the influences of obstacles on the charging process. Secondly, we propose a new charging group division algorithm, which can select the sets of the sensor nodes that can be charged simultaneously and determine the selection ranges of the charging spots. Thirdly, we propose a charging spots selection algorithm based on the FDM, which can not only reduce the number of sensor failures, but also guarantee the high-level charging utility. Fourthly, we propose a dynamic zonal collaborative charging scheduling scheme. It divides the charging zones to achieve balanced distribution of the charging loads. When a zone is not schedulable, our scheme will redistribute its high energy-cost charging tasks to the zone with less load for dynamic adjustment. When some charging tasks can not be adjusted, our scheme will discard the ones with less contribution, minimizing the losses of the network. Finally, we conduct a large number of simulations to verify the performances of our work. The simulation results show that our scheme has obviously better performances compared with the other arts. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Wireless Networks (10220038) is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11276-023-03402-9
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        Text: English
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      – SubjectFull: Fresnel diffraction
        Type: general
      – SubjectFull: Dynamic loads
        Type: general
      – SubjectFull: Wireless sensor networks
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      – SubjectFull: Job performance
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      – SubjectFull: Scheduling
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      – SubjectFull: Detectors
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              M: 08
              Text: Aug2024
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              Y: 2024
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