Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks
Recently, energy harvesting has been emerging as a promising technique to prolong the lifetime for wireless sensor nodes. Most existing efforts address the design of energy harvesting and sensor node subsystem separately or ignore some real-world constraints. In this paper, we study how to codesign...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-06-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2014/250236 |
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| _version_ | 1850158205929259008 |
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| author | Xi Jin Fanxin Kong Peng Zeng Qingxu Deng Huiting Xu |
| author_facet | Xi Jin Fanxin Kong Peng Zeng Qingxu Deng Huiting Xu |
| author_sort | Xi Jin |
| collection | DOAJ |
| description | Recently, energy harvesting has been emerging as a promising technique to prolong the lifetime for wireless sensor nodes. Most existing efforts address the design of energy harvesting and sensor node subsystem separately or ignore some real-world constraints. In this paper, we study how to codesign the two subsystems and how to jointly manage energy harvesting, storage, and usage. We first propose a novel system architecture for energy harvesting which employs several supercapacitors to eliminate the conflicts on charging and discharging among different system components. Then, we present a method to schedule their charging and discharging, which is proved to be able to guarantee zero waste of the harvested energy if the battery is not full. Third, we propose an optimal algorithm to minimize different components’ capacity and two heuristic algorithms to maximize the system reward. We conduct extensive experiments based on real-life data traces. Results show that the proposed system architecture can harvest more energy compared to the state of the art, and the capacity optimization algorithm can choose the most suitable size for each system component. |
| format | Article |
| id | doaj-art-6af910350e47496ba6daf04456a45bb1 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2014-06-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-6af910350e47496ba6daf04456a45bb12025-08-20T02:23:57ZengWileyInternational Journal of Distributed Sensor Networks1550-14772014-06-011010.1155/2014/250236250236Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor NetworksXi Jin0Fanxin Kong1Peng Zeng2Qingxu Deng3Huiting Xu4 Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang 110016, China School of Computer Science, McGill University, QC, Canada, H3A 0E9 Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang 110016, China College of Information Science and Engineering, Northeastern University, Shenyang 110819, China College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaRecently, energy harvesting has been emerging as a promising technique to prolong the lifetime for wireless sensor nodes. Most existing efforts address the design of energy harvesting and sensor node subsystem separately or ignore some real-world constraints. In this paper, we study how to codesign the two subsystems and how to jointly manage energy harvesting, storage, and usage. We first propose a novel system architecture for energy harvesting which employs several supercapacitors to eliminate the conflicts on charging and discharging among different system components. Then, we present a method to schedule their charging and discharging, which is proved to be able to guarantee zero waste of the harvested energy if the battery is not full. Third, we propose an optimal algorithm to minimize different components’ capacity and two heuristic algorithms to maximize the system reward. We conduct extensive experiments based on real-life data traces. Results show that the proposed system architecture can harvest more energy compared to the state of the art, and the capacity optimization algorithm can choose the most suitable size for each system component.https://doi.org/10.1155/2014/250236 |
| spellingShingle | Xi Jin Fanxin Kong Peng Zeng Qingxu Deng Huiting Xu Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks |
| title_full | Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks |
| title_fullStr | Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks |
| title_full_unstemmed | Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks |
| title_short | Joint Management of Energy Harvesting, Storage, and Usage for Green Wireless Sensor Networks |
| title_sort | joint management of energy harvesting storage and usage for green wireless sensor networks |
| url | https://doi.org/10.1155/2014/250236 |
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