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A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy

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dc.contributor.author Ntshabele, K
dc.contributor.author Isong, B
dc.contributor.author Abu-Mahfouz, Adnan MI
dc.date.accessioned 2022-02-21T08:21:29Z
dc.date.available 2022-02-21T08:21:29Z
dc.date.issued 2021-12
dc.identifier.citation Ntshabele, K., Isong, B. & Abu-Mahfouz, A.M. 2021. A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy. http://hdl.handle.net/10204/12281 . en_ZA
dc.identifier.isbn 978-1-6654-4231-2
dc.identifier.uri 978-1-6654-4232-9
dc.identifier.uri DOI: 10.1109/ICECET52533.2021.9698565
dc.identifier.uri http://hdl.handle.net/10204/12281
dc.description.abstract Inefficient energy utilization in the cognitive radio sensor networks (CRSNs) is a serious challenge that adversely affects its performance and quality of service (QoS). Several different strategies and mechanisms have been proposed and developed to address the rapid energy depletion faced by cognitive sensor nodes. However, optimum energy efficiency is yet to be fully realized in the CRSN. Therefore, this paper proposes an energy-efficient scheduling mechanism for CRSNs that is based on both the K-Means clustering and Sensor-Medium Access Control (S-MAC) protocol to minimize high energy utilization. The K-Means algorithm clusters the cognitive sensor nodes to minimize the overall network complexities while the S-MAC protocol performs periodic data transfer and sleep-wake cycles to regulate data flow and minimize interferences. Simulations were performed to analyze the design using six different S-MAC's duty cycles based on throughput, the average energy used, the residual energy, and delay as metrics. This was used to identify the optimal duty cycle for energy-efficient CRSN implementation. Results obtained revealed a 10% duty cycle as the most suitable energy-efficient approach in terms of the metrics considered. We, therefore, recommend a 10% duty cycle for the implementation in designing an energy-efficient model in CRSNs. en_US
dc.format Abstract en_US
dc.language.iso en en_US
dc.relation.uri https://ieeexplore.ieee.org/document/9698565 en_US
dc.source 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), Cape Town, South Africa, 9-10 December 2021 en_US
dc.subject Clustering en_US
dc.subject Cognitive radio sensor networks en_US
dc.subject CRSN en_US
dc.subject Energy efficiency en_US
dc.subject Sensor-Medium Access Control en_US
dc.subject S-MAC en_US
dc.subject Wireless sensor network en_US
dc.subject WSN en_US
dc.title A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy en_US
dc.type Conference Presentation en_US
dc.description.pages 7 en_US
dc.description.note Copyright: 2021 IEEE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website: https://ieeexplore.ieee.org/document/9698565 en_US
dc.description.cluster Next Generation Enterprises & Institutions en_US
dc.description.impactarea EDT4IR Management en_US
dc.identifier.apacitation Ntshabele, K., Isong, B., & Abu-Mahfouz, A. M. (2021). A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy. http://hdl.handle.net/10204/12281 en_ZA
dc.identifier.chicagocitation Ntshabele, K, B Isong, and Adnan MI Abu-Mahfouz. "A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy." <i>2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), Cape Town, South Africa, 9-10 December 2021</i> (2021): http://hdl.handle.net/10204/12281 en_ZA
dc.identifier.vancouvercitation Ntshabele K, Isong B, Abu-Mahfouz AM, A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy; 2021. http://hdl.handle.net/10204/12281 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Ntshabele, K AU - Isong, B AU - Abu-Mahfouz, Adnan MI AB - Inefficient energy utilization in the cognitive radio sensor networks (CRSNs) is a serious challenge that adversely affects its performance and quality of service (QoS). Several different strategies and mechanisms have been proposed and developed to address the rapid energy depletion faced by cognitive sensor nodes. However, optimum energy efficiency is yet to be fully realized in the CRSN. Therefore, this paper proposes an energy-efficient scheduling mechanism for CRSNs that is based on both the K-Means clustering and Sensor-Medium Access Control (S-MAC) protocol to minimize high energy utilization. The K-Means algorithm clusters the cognitive sensor nodes to minimize the overall network complexities while the S-MAC protocol performs periodic data transfer and sleep-wake cycles to regulate data flow and minimize interferences. Simulations were performed to analyze the design using six different S-MAC's duty cycles based on throughput, the average energy used, the residual energy, and delay as metrics. This was used to identify the optimal duty cycle for energy-efficient CRSN implementation. Results obtained revealed a 10% duty cycle as the most suitable energy-efficient approach in terms of the metrics considered. We, therefore, recommend a 10% duty cycle for the implementation in designing an energy-efficient model in CRSNs. DA - 2021-12 DB - ResearchSpace DP - CSIR J1 - 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), Cape Town, South Africa, 9-10 December 2021 KW - Clustering KW - Cognitive radio sensor networks KW - CRSN KW - Energy efficiency KW - Sensor-Medium Access Control KW - S-MAC KW - Wireless sensor network KW - WSN LK - https://researchspace.csir.co.za PY - 2021 SM - 978-1-6654-4231-2 T1 - A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy TI - A mechanism for energy efficiency in cognitive radio sensor networks based on sleep-wake scheduling strategy UR - http://hdl.handle.net/10204/12281 ER - en_ZA
dc.identifier.worklist 25419 en_US


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