Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks
Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harv...
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| Format: | Article |
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MDPI AG
2017-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/17/9/1933 |
| _version_ | 1797999459471196160 |
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| author | Ya Gao Wenchi Cheng Hailin Zhang |
| author_facet | Ya Gao Wenchi Cheng Hailin Zhang |
| author_sort | Ya Gao |
| collection | DOAJ |
| description | Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks. |
| first_indexed | 2024-04-11T11:04:58Z |
| format | Article |
| id | doaj.art-40ae5a29c00547448bc8af1e644d5524 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T11:04:58Z |
| publishDate | 2017-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-40ae5a29c00547448bc8af1e644d55242022-12-22T04:28:24ZengMDPI AGSensors1424-82202017-08-01179193310.3390/s17091933s17091933Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor NetworksYa Gao0Wenchi Cheng1Hailin Zhang2State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, ChinaState Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, ChinaState Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710071, ChinaEnergy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks.https://www.mdpi.com/1424-8220/17/9/1933energy harvestingquality of service (QoS)power controlenergy efficiency optimizationwireless sensor networks |
| spellingShingle | Ya Gao Wenchi Cheng Hailin Zhang Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks Sensors energy harvesting quality of service (QoS) power control energy efficiency optimization wireless sensor networks |
| title | Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks |
| title_full | Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks |
| title_fullStr | Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks |
| title_full_unstemmed | Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks |
| title_short | Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks |
| title_sort | statistical qos guaranteed energy efficiency optimization for energy harvesting wireless sensor networks |
| topic | energy harvesting quality of service (QoS) power control energy efficiency optimization wireless sensor networks |
| url | https://www.mdpi.com/1424-8220/17/9/1933 |
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