Multi-objective and Randomly Distributed Fuzzy Logic-Based Unequal Clustering in Heterogeneous Wireless Sensor Networks
Paper
Adnan, Mohd, Ahmad, Tazeem, Rafi, Saima, Abdullah and Vurity, Anudeep. 2024. "Multi-objective and Randomly Distributed Fuzzy Logic-Based Unequal Clustering in Heterogeneous Wireless Sensor Networks." 16th International Conference on Computational Collective Intelligence (ICCCI 2024). Leipzig, Germany 09 - 11 Sep 2024 Switzerland . Springer. https://doi.org/10.1007/978-3-031-70816-9_26
| Paper/Presentation Title | Multi-objective and Randomly Distributed Fuzzy Logic-Based Unequal Clustering in Heterogeneous Wireless Sensor Networks |
|---|---|
| Presentation Type | Paper |
| Authors | Adnan, Mohd, Ahmad, Tazeem, Rafi, Saima, Abdullah and Vurity, Anudeep |
| Journal or Proceedings Title | Proceedings of the 16th International Conference on Computational Collective Intelligence (ICCCI 2024) |
| Journal Citation | 14810, pp. 332-345 |
| Number of Pages | 14 |
| Year | 2024 |
| Publisher | Springer |
| Place of Publication | Switzerland |
| Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-031-70816-9_26 |
| Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/978-3-031-70816-9_26 |
| Web Address (URL) of Conference Proceedings | https://link.springer.com/book/10.1007/978-3-031-70816-9 |
| Conference/Event | 16th International Conference on Computational Collective Intelligence (ICCCI 2024) |
| Event Details | 16th International Conference on Computational Collective Intelligence (ICCCI 2024) Delivery In person Event Date 09 to end of 11 Sep 2024 Event Location Leipzig, Germany |
| Abstract | Wireless Sensor Networks (WSNs) are a crucial component in the fabric of the Internet of Things (IoT) ecosystem, enabling a myriad of applications ranging from environmental monitoring to precision agriculture and smart cities. However, these sensors are constrained in terms of energy, computing power, and storage which makes reliable communication a critical research challenge. To address these challenges, unequal clustering has emerged as a promising solution where clusters are intentionally formed with varying sizes to accommodate heterogeneous capabilities and energy demands across the network. In this paper, we introduce a novel Multi-Objective and Randomly Distributed Fuzzy Logic-based Unequal Clustering (MORF-UC) scheme to address the challenge of energy management and hotspot issues in WSNs. By leveraging fuzzy logic to account for variables such as distance to the base station (BS), residual energy, node concentration, and data forwarding ratio of nodes, this scheme aims to extend network lifetime, energy use, and data transmission reliability while mitigating the hot spot issues. Simulation results demonstrate that the proposed methodology outperforms existing methods such as TTDFP and MOUOC in the energy conservation, network lifetime extension, and throughput enhancement, thereby offering a significant advancement in the field of WSN optimization. |
| Keywords | Wireless sensor networks; Unequal clustering; Fuzzy logic; Network lifetime; Multi-objective; Network scalability |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 400608. Wireless communication systems and technologies (incl. microwave and millimetrewave) |
| Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
| Series | Lecture Notes in Computer Science |
| Byline Affiliations | Inha University, Korea |
| University of Southern Queensland | |
| Edinburgh Napier University, Untied States | |
| PETRONAS University of Technology, Malaysia | |
| George Mason University, United States |
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https://research.usq.edu.au/item/zqz62/multi-objective-and-randomly-distributed-fuzzy-logic-based-unequal-clustering-in-heterogeneous-wireless-sensor-networks
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