Monitoring and enhancing the co-operation of IoT network rhrough scheduling function based punishment reward strategy

The Internet of Things (IoT) has revolutionized the connectivity of physical devices, leading to an exponential increase in multimedia wireless traffic and creating substantial demand for radio spectrum. Given the inherent scarcity of available spectrum, Cognitive Radio (CR)-assisted IoT emerges as a promising solution to optimize spectrum utilization through cooperation between cognitive and IoT nodes. Unlicensed IoT nodes can opportunistically access licensed spectrum bands without causing interference to licensed users. However, energy constraints may lead to reduced cooperation from IoT nodes during the search for vacant channels, as they aim to conserve battery life. To address this issue, we propose a Punishment-reward-based Cooperative Sensing and Data Forwarding (PR-CSDF) approach for IoT data transmission. Our method involves two key steps: (1) distributing sensing tasks among IoT nodes and (2) enhancing cooperation through a reward and punishment strategy. Evaluation results demonstrate that both secondary users (SUs) and IoT nodes achieve significant utility gains with the proposed mechanism, providing strong incentives for cooperative behaviour.

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Publication Details

Journal
PLoS ONE
Published
2024-09-19
DOI
https://doi.org/10.1371/journal.pone.0309123
Citations
1
Primary Topic
Cognitive Radio Networks and Spectrum Sensing
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article
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0.35
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article

Monitoring and enhancing the co-operation of IoT network rhrough scheduling function based punishment reward strategy

Abdur Rashid Sangi, Satish Anamalamudi, Anil Carie, Bingqian Li
1 citations
PLoS ONE
Cognitive Radio Networks and Spectrum Sensing
0.35
article

Monitoring and enhancing the co-operation of IoT network rhrough scheduling function based punishment reward strategy

Abdur Rashid Sangi, Satish Anamalamudi, Anil Carie, Bingqian Li
article en
1 citations

Abstract

The Internet of Things (IoT) has revolutionized the connectivity of physical devices, leading to an exponential increase in multimedia wireless traffic and creating substantial demand for radio spectrum. Given the inherent scarcity of available spectrum, Cognitive Radio (CR)-assisted IoT emerges as a promising solution to optimize spectrum utilization through cooperation between cognitive and IoT nodes. Unlicensed IoT nodes can opportunistically access licensed spectrum bands without causing interference to licensed users. However, energy constraints may lead to reduced cooperation from IoT nodes during the search for vacant channels, as they aim to conserve battery life. To address this issue, we propose a Punishment-reward-based Cooperative Sensing and Data Forwarding (PR-CSDF) approach for IoT data transmission. Our method involves two key steps: (1) distributing sensing tasks among IoT nodes and (2) enhancing cooperation through a reward and punishment strategy. Evaluation results demonstrate that both secondary users (SUs) and IoT nodes achieve significant utility gains with the proposed mechanism, providing strong incentives for cooperative behaviour.

PLoS ONEVol. 19(9)
Soochow University (CN), SRM University (IN), Wenzhou-Kean University (CN), Kean University (US)
Partnerships for the goals
Openalex Percentile: Top 39%
Cognitive Radio Networks and Spectrum Sensing
0.35
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