An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs)
Recent studies have highlighted the importance of implementing clustering schemes in Wireless Body Area Networks (WBANs) to address challenges such as scalability, network topology changes, spectrum scarcity, and management. However, many existing approaches focus only on conventional performance me...
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IEEE
2024-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10741227/ |
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| author | Rasmita Kumari Mohanty Chinimilli Venkata Rama Padmaja Suresh Kumar Kanaparthi Srinivas Kanakala K. Ravikiran Janjhyam Venkata Naga Ramesh Sachi Nandan Mohanty Mukkoti Maruthi Venkata Chalapathi |
| author_facet | Rasmita Kumari Mohanty Chinimilli Venkata Rama Padmaja Suresh Kumar Kanaparthi Srinivas Kanakala K. Ravikiran Janjhyam Venkata Naga Ramesh Sachi Nandan Mohanty Mukkoti Maruthi Venkata Chalapathi |
| author_sort | Rasmita Kumari Mohanty |
| collection | DOAJ |
| description | Recent studies have highlighted the importance of implementing clustering schemes in Wireless Body Area Networks (WBANs) to address challenges such as scalability, network topology changes, spectrum scarcity, and management. However, many existing approaches focus only on conventional performance metrics and overlook the integration of spectrum trading and efficient spectrum utilization. This paper proposes a novel clustering control scheme based on fuzzy logic and Nash equilibrium to enhance scalability, network stability, and resource management in WBANs. Our approach employs multi-criteria decision-making to optimize cluster head (CH) selection and routing strategies using reinforcement learning to achieve quality of service (QoS). Additionally, a secure lightweight Diffie-Hellman key exchange is used to protect data transmission. The proposed protocol outperforms existing protocols, including TAFLR, EQRSRL, and SEBA, in terms of throughput (3.2 kbps), packet delivery ratio (93%), delay (0.31 s), cluster efficiency (95%), and energy consumption (0.43 J). |
| format | Article |
| id | doaj-art-5c2d54c18f5d4669a1c47a89b2f95e5d |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-5c2d54c18f5d4669a1c47a89b2f95e5d2024-11-12T00:01:11ZengIEEEIEEE Access2169-35362024-01-011216319816322310.1109/ACCESS.2024.348963110741227An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs)Rasmita Kumari Mohanty0https://orcid.org/0000-0002-5828-5649Chinimilli Venkata Rama Padmaja1Suresh Kumar Kanaparthi2Srinivas Kanakala3https://orcid.org/0000-0003-0687-4748K. Ravikiran4https://orcid.org/0000-0002-7610-1890Janjhyam Venkata Naga Ramesh5https://orcid.org/0000-0002-2084-8864Sachi Nandan Mohanty6https://orcid.org/0000-0002-4939-0797Mukkoti Maruthi Venkata Chalapathi7https://orcid.org/0000-0001-5528-7844Department of CSE-(CyS, DS) and AI&DS, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, IndiaDepartment of Computer Science and Engineering, Institute of Aeronautical Engineering, Hyderabad, IndiaDepartment of Computer Science and Engineering, SRM University AP, Amaravati, Andhra Pradesh, IndiaDepartment of Computer Science and Engineering, Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering and Technology, Hyderabad, Telangana, IndiaDepartment of Information Technology, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana, IndiaDepartment of Computer Science and Engineering, Graphic Era Hill University, Dehradun, IndiaSchool of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, IndiaSchool of Computer Science and Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, IndiaRecent studies have highlighted the importance of implementing clustering schemes in Wireless Body Area Networks (WBANs) to address challenges such as scalability, network topology changes, spectrum scarcity, and management. However, many existing approaches focus only on conventional performance metrics and overlook the integration of spectrum trading and efficient spectrum utilization. This paper proposes a novel clustering control scheme based on fuzzy logic and Nash equilibrium to enhance scalability, network stability, and resource management in WBANs. Our approach employs multi-criteria decision-making to optimize cluster head (CH) selection and routing strategies using reinforcement learning to achieve quality of service (QoS). Additionally, a secure lightweight Diffie-Hellman key exchange is used to protect data transmission. The proposed protocol outperforms existing protocols, including TAFLR, EQRSRL, and SEBA, in terms of throughput (3.2 kbps), packet delivery ratio (93%), delay (0.31 s), cluster efficiency (95%), and energy consumption (0.43 J).https://ieeexplore.ieee.org/document/10741227/Clusteringmulti-objective decisionsgame theoryNash equilibriumreinforcement learning |
| spellingShingle | Rasmita Kumari Mohanty Chinimilli Venkata Rama Padmaja Suresh Kumar Kanaparthi Srinivas Kanakala K. Ravikiran Janjhyam Venkata Naga Ramesh Sachi Nandan Mohanty Mukkoti Maruthi Venkata Chalapathi An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) IEEE Access Clustering multi-objective decisions game theory Nash equilibrium reinforcement learning |
| title | An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) |
| title_full | An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) |
| title_fullStr | An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) |
| title_full_unstemmed | An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) |
| title_short | An Efficient Game Theory Based Multi-Objective Decision and Clustering (EGMDC) for Wireless Body Area Networks (WBANs) |
| title_sort | efficient game theory based multi objective decision and clustering egmdc for wireless body area networks wbans |
| topic | Clustering multi-objective decisions game theory Nash equilibrium reinforcement learning |
| url | https://ieeexplore.ieee.org/document/10741227/ |
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