A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks
<p dir="ltr">Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Cooperative communicati...
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2022
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| _version_ | 1864513531093712896 |
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| author | Kanthavel Radhakrishnan (17542101) |
| author2 | Dhaya Ramakrishnan (17542104) Osamah Ibrahim Khalaf (17542107) Mueen Uddin (4903510) Chin-Ling Chen (17542074) Chih-Ming Wu (17542092) |
| author2_role | author author author author author |
| author_facet | Kanthavel Radhakrishnan (17542101) Dhaya Ramakrishnan (17542104) Osamah Ibrahim Khalaf (17542107) Mueen Uddin (4903510) Chin-Ling Chen (17542074) Chih-Ming Wu (17542092) |
| author_role | author |
| dc.creator.none.fl_str_mv | Kanthavel Radhakrishnan (17542101) Dhaya Ramakrishnan (17542104) Osamah Ibrahim Khalaf (17542107) Mueen Uddin (4903510) Chin-Ling Chen (17542074) Chih-Ming Wu (17542092) |
| dc.date.none.fl_str_mv | 2022-06-13T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/s22124475 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_Novel_Deep_Learning-Based_Cooperative_Communication_Channel_Model_for_Wireless_Underground_Sensor_Networks/24717543 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electronics, sensors and digital hardware Information and computing sciences Distributed computing and systems software Machine learning wireless underground sensor networks deep learning based cooperative communication channel multi-input-single-output |
| dc.title.none.fl_str_mv | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Cooperative communication channel model for Wireless Underground Sensor Networks for accurate and reliable monitoring in hostile underground locations. Furthermore, the proposed communication model aims at the effective utilization of cluster-based Cooperative models through the relay nodes. However, by keeping the cost effectiveness, reliability, and user-friendliness of wireless underground sensor networks through inter-cluster Cooperative transmission between two cluster heads, the determination of the overall energy performance is also measured. The energy co-operative channel allocation routing (ECCAR), Energy Hierarchical Optimistic Routing (EHOR), Non-Cooperative, and Dynamic Energy Routing (DER) methods were used to figure out how well the proposed WUSN works. The Quality of Service (QoS) parameters such as transmission time, throughput, packet loss, and efficiency were used in order to evaluate the performance of the proposed WUSNs. From the simulation results, it is apparently seen that the proposed system demonstrates some superiority over other methods in terms of its better energy utilization of 89.71%, Packet Delivery ratio of 78.2%, Average Packet Delay of 82.3%, Average Network overhead of 77.4%, data packet throughput of 83.5% and an average system packet loss of 91%.</p><h2>Other Information</h2><p dir="ltr">Published in: Sensors<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/s22124475" target="_blank">https://dx.doi.org/10.3390/s22124475</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_f4990a80a53d19e5280ba43848e15cd5 |
| identifier_str_mv | 10.3390/s22124475 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24717543 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor NetworksKanthavel Radhakrishnan (17542101)Dhaya Ramakrishnan (17542104)Osamah Ibrahim Khalaf (17542107)Mueen Uddin (4903510)Chin-Ling Chen (17542074)Chih-Ming Wu (17542092)EngineeringElectronics, sensors and digital hardwareInformation and computing sciencesDistributed computing and systems softwareMachine learningwireless underground sensor networksdeep learning based cooperative communication channelmulti-input-single-output<p dir="ltr">Wireless Underground Sensor Networks (WUSNs) have been showing prospective supervising application domains in the underground region of the earth through sensing, computation, and communication. This paper presents a novel Deep Learning (DL)-based Cooperative communication channel model for Wireless Underground Sensor Networks for accurate and reliable monitoring in hostile underground locations. Furthermore, the proposed communication model aims at the effective utilization of cluster-based Cooperative models through the relay nodes. However, by keeping the cost effectiveness, reliability, and user-friendliness of wireless underground sensor networks through inter-cluster Cooperative transmission between two cluster heads, the determination of the overall energy performance is also measured. The energy co-operative channel allocation routing (ECCAR), Energy Hierarchical Optimistic Routing (EHOR), Non-Cooperative, and Dynamic Energy Routing (DER) methods were used to figure out how well the proposed WUSN works. The Quality of Service (QoS) parameters such as transmission time, throughput, packet loss, and efficiency were used in order to evaluate the performance of the proposed WUSNs. From the simulation results, it is apparently seen that the proposed system demonstrates some superiority over other methods in terms of its better energy utilization of 89.71%, Packet Delivery ratio of 78.2%, Average Packet Delay of 82.3%, Average Network overhead of 77.4%, data packet throughput of 83.5% and an average system packet loss of 91%.</p><h2>Other Information</h2><p dir="ltr">Published in: Sensors<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/s22124475" target="_blank">https://dx.doi.org/10.3390/s22124475</a></p><p dir="ltr">Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.</p>2022-06-13T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/s22124475https://figshare.com/articles/journal_contribution/A_Novel_Deep_Learning-Based_Cooperative_Communication_Channel_Model_for_Wireless_Underground_Sensor_Networks/24717543CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247175432022-06-13T06:00:00Z |
| spellingShingle | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks Kanthavel Radhakrishnan (17542101) Engineering Electronics, sensors and digital hardware Information and computing sciences Distributed computing and systems software Machine learning wireless underground sensor networks deep learning based cooperative communication channel multi-input-single-output |
| status_str | publishedVersion |
| title | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| title_full | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| title_fullStr | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| title_full_unstemmed | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| title_short | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| title_sort | A Novel Deep Learning-Based Cooperative Communication Channel Model for Wireless Underground Sensor Networks |
| topic | Engineering Electronics, sensors and digital hardware Information and computing sciences Distributed computing and systems software Machine learning wireless underground sensor networks deep learning based cooperative communication channel multi-input-single-output |