An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems
The energy consumption and coverage range of unmanned aerial vehicles (UAVs) are major challenges in UAV-based postdisaster communications. To address these challenges, energy harvesting is employed to power communication devices and prolong the lifetime of the wireless communication network during...
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my.um.eprints.286412022-04-06T05:37:04Z http://eprints.um.edu.my/28641/ An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems Saif, Abdu Dimyati, Kaharudin Noordin, Kamarul Ariffin Deepak, G. C. Shah, Nor Shahida Mohd Abdullah, Qazwan Mohamad, Mahathir QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering The energy consumption and coverage range of unmanned aerial vehicles (UAVs) are major challenges in UAV-based postdisaster communications. To address these challenges, energy harvesting is employed to power communication devices and prolong the lifetime of the wireless communication network during a disaster. In addition, clustering techniques and device-to-device (D2D) communication are needed to increase the overall network coverage and provide sustainable connectivity during the disaster and postdisaster phases. We have proposed a novel emergency communication system (ECS) using the optimal cluster head (CH) technique to improve the energy transfer efficiency for sustainable network connectivity. We have developed a UAV deployment model assisted by the clustering technique and D2D links that is capable of harvesting energy to increase the network lifetime. This new approach is expected to enhance the reliability of the network in disaster situations. The proposed methods have been evaluated by measuring the energy efficiency performance and the network outage probability. The simulation results demonstrate improved performance with the deployment of optimal CHs, while the outage probability has been effectively reduced. Moreover, the proposed approach has been proven to reduce the computational complexity. In conclusion, UAV deployment with the optimal CH algorithm is a suitable network design to recover from natural disasters and potentially save many lives. Institute of Electrical and Electronics Engineers 2021 Article PeerReviewed Saif, Abdu and Dimyati, Kaharudin and Noordin, Kamarul Ariffin and Deepak, G. C. and Shah, Nor Shahida Mohd and Abdullah, Qazwan and Mohamad, Mahathir (2021) An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems. IEEE Access, 9. pp. 78188-78202. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2021.3083640 <https://doi.org/10.1109/ACCESS.2021.3083640>. 10.1109/ACCESS.2021.3083640 |
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QA75 Electronic computers. Computer science TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Saif, Abdu Dimyati, Kaharudin Noordin, Kamarul Ariffin Deepak, G. C. Shah, Nor Shahida Mohd Abdullah, Qazwan Mohamad, Mahathir An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
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The energy consumption and coverage range of unmanned aerial vehicles (UAVs) are major challenges in UAV-based postdisaster communications. To address these challenges, energy harvesting is employed to power communication devices and prolong the lifetime of the wireless communication network during a disaster. In addition, clustering techniques and device-to-device (D2D) communication are needed to increase the overall network coverage and provide sustainable connectivity during the disaster and postdisaster phases. We have proposed a novel emergency communication system (ECS) using the optimal cluster head (CH) technique to improve the energy transfer efficiency for sustainable network connectivity. We have developed a UAV deployment model assisted by the clustering technique and D2D links that is capable of harvesting energy to increase the network lifetime. This new approach is expected to enhance the reliability of the network in disaster situations. The proposed methods have been evaluated by measuring the energy efficiency performance and the network outage probability. The simulation results demonstrate improved performance with the deployment of optimal CHs, while the outage probability has been effectively reduced. Moreover, the proposed approach has been proven to reduce the computational complexity. In conclusion, UAV deployment with the optimal CH algorithm is a suitable network design to recover from natural disasters and potentially save many lives. |
format |
Article |
author |
Saif, Abdu Dimyati, Kaharudin Noordin, Kamarul Ariffin Deepak, G. C. Shah, Nor Shahida Mohd Abdullah, Qazwan Mohamad, Mahathir |
author_facet |
Saif, Abdu Dimyati, Kaharudin Noordin, Kamarul Ariffin Deepak, G. C. Shah, Nor Shahida Mohd Abdullah, Qazwan Mohamad, Mahathir |
author_sort |
Saif, Abdu |
title |
An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
title_short |
An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
title_full |
An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
title_fullStr |
An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
title_full_unstemmed |
An efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
title_sort |
efficient energy harvesting and optimal clustering technique for sustainable postdisaster emergency communication systems |
publisher |
Institute of Electrical and Electronics Engineers |
publishDate |
2021 |
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http://eprints.um.edu.my/28641/ |
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1735409566595678208 |
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13.18916 |