Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks
Energy saving is often achieved via “squeezing” other application-sensitive Quality of Service (QoS) parameters such as delay and throughput. Accordingly, energy-saving methods must consider those QoS parameters. In this paper, we survey the most recent work on energy efficiency in WSNs and we discu...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi - SAGE Publishing
2016-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2016/1576038 |
| _version_ | 1797763232045203456 |
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| author | Mohamed Abdelaal Oliver Theel Christian Kuka Peilin Zhang Yang Gao Vasilisa Bashlovkina Daniela Nicklas Martin Fränzle |
| author_facet | Mohamed Abdelaal Oliver Theel Christian Kuka Peilin Zhang Yang Gao Vasilisa Bashlovkina Daniela Nicklas Martin Fränzle |
| author_sort | Mohamed Abdelaal |
| collection | DOAJ |
| description | Energy saving is often achieved via “squeezing” other application-sensitive Quality of Service (QoS) parameters such as delay and throughput. Accordingly, energy-saving methods must consider those QoS parameters. In this paper, we survey the most recent work on energy efficiency in WSNs and we discuss the impacts of these methods on the QoS provided. Moreover, we propose a novel divide-and-conquer procedure to deal with the trade-off between energy consumption and other QoS parameters. The idea is to tackle a certain source of energy consumption to minimize the drawn energy. Subsequently, this energy-saving method is refined to consider other service qualities. To support the correctness of our claim, three energy-saving methods, taking the QoS issues into consideration, are given as examples. The first method exploits a so-called Fuzzy transform for shrinking the wireless traffic with highly precise lossy data compression. In the second method, the sensing module is targeted by employing reliable virtual sensors. Such sensors compensate the unavailability of main energy-hungry sensors during sleep periods. The third method exploits a self-adaptive mechanism to improve the QoS parameters via deliberately reducing the lifetime below the maximum time and exploiting design-time knowledge. |
| first_indexed | 2024-03-12T19:38:38Z |
| format | Article |
| id | doaj.art-a8ff1e60a5f8413bb0e65391eec8603c |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T19:38:38Z |
| publishDate | 2016-05-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-a8ff1e60a5f8413bb0e65391eec8603c2023-08-02T03:59:22ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-05-011210.1155/2016/1576038Improving Energy Efficiency in QoS-Constrained Wireless Sensor NetworksMohamed Abdelaal0Oliver Theel1Christian Kuka2Peilin Zhang3Yang Gao4Vasilisa Bashlovkina5Daniela Nicklas6Martin Fränzle7 Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, Germany Grinnell College, Grinnell, IA 50112, USA University of Bamberg, 96047 Bamberg, Germany Carl von Ossietzky University of Oldenburg, 26129 Oldenburg, GermanyEnergy saving is often achieved via “squeezing” other application-sensitive Quality of Service (QoS) parameters such as delay and throughput. Accordingly, energy-saving methods must consider those QoS parameters. In this paper, we survey the most recent work on energy efficiency in WSNs and we discuss the impacts of these methods on the QoS provided. Moreover, we propose a novel divide-and-conquer procedure to deal with the trade-off between energy consumption and other QoS parameters. The idea is to tackle a certain source of energy consumption to minimize the drawn energy. Subsequently, this energy-saving method is refined to consider other service qualities. To support the correctness of our claim, three energy-saving methods, taking the QoS issues into consideration, are given as examples. The first method exploits a so-called Fuzzy transform for shrinking the wireless traffic with highly precise lossy data compression. In the second method, the sensing module is targeted by employing reliable virtual sensors. Such sensors compensate the unavailability of main energy-hungry sensors during sleep periods. The third method exploits a self-adaptive mechanism to improve the QoS parameters via deliberately reducing the lifetime below the maximum time and exploiting design-time knowledge.https://doi.org/10.1155/2016/1576038 |
| spellingShingle | Mohamed Abdelaal Oliver Theel Christian Kuka Peilin Zhang Yang Gao Vasilisa Bashlovkina Daniela Nicklas Martin Fränzle Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks |
| title_full | Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks |
| title_fullStr | Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks |
| title_full_unstemmed | Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks |
| title_short | Improving Energy Efficiency in QoS-Constrained Wireless Sensor Networks |
| title_sort | improving energy efficiency in qos constrained wireless sensor networks |
| url | https://doi.org/10.1155/2016/1576038 |
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