FCM-OR: A Local Density-Aware Opportunistic Routing Protocol for Energy-Efficient Wireless Sensor Networks

Wireless sensor networks (WSNs) face a fundamental challenge: their sensors run on batteries, making energy efficiency crucial. While researchers have tried to extend network lifespans by improving routing and access control protocols across different layers, this remains a complex issue. One promising solution is opportunistic routing (OR), which uses multiple nodes to relay data. This approach reduces how long senders must wait for a specific next-hop node and helps prevent data loss from collisions. That said, choosing which nodes should act as forwarders can greatly affect how well the network performs. To tackle this problem, we developed a new approach called FCM-OR, a local density-based forwarder selection algorithm for opportunistic routing in WSNs. Our algorithm is particularly effective in networks where sensors are not evenly spread out and are densely packed. It uses fuzzy c-means (FCM) clustering to smartly pick the best forwarders based on how many nodes are nearby. By focusing on the sender’s immediate surroundings, FCM-OR helps solve the problems that arise when different parts of the network have varying densities of nodes. We also created a new way to measure routing effectiveness called “forwarding rank”. To test how well our protocol works, we ran extensive simulations comparing it to existing methods, including opportunistic routing with duty-cycled WSNs and load-balanced opportunistic routing. The results are clear: FCM-OR significantly improves both network performance and energy efficiency, especially in networks where nodes are not uniformly distributed.

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Publication Details

Journal
Electronics
Published
2025-04-30
DOI
https://doi.org/10.3390/electronics14091841
Citations
3
Primary Topic
Energy Efficient Wireless Sensor Networks
Type
article
Field-Weighted Citation Impact
4.46

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article

FCM-OR: A Local Density-Aware Opportunistic Routing Protocol for Energy-Efficient Wireless Sensor Networks

Seokjoo Shin, Ayesha Akter Lata, Moonsoo Kang
3 citations
Electronics
Energy Efficient Wireless Sensor Networks
4.46
article

FCM-OR: A Local Density-Aware Opportunistic Routing Protocol for Energy-Efficient Wireless Sensor Networks

Seokjoo Shin, Ayesha Akter Lata, Moonsoo Kang
article en
3 citations

Abstract

Wireless sensor networks (WSNs) face a fundamental challenge: their sensors run on batteries, making energy efficiency crucial. While researchers have tried to extend network lifespans by improving routing and access control protocols across different layers, this remains a complex issue. One promising solution is opportunistic routing (OR), which uses multiple nodes to relay data. This approach reduces how long senders must wait for a specific next-hop node and helps prevent data loss from collisions. That said, choosing which nodes should act as forwarders can greatly affect how well the network performs. To tackle this problem, we developed a new approach called FCM-OR, a local density-based forwarder selection algorithm for opportunistic routing in WSNs. Our algorithm is particularly effective in networks where sensors are not evenly spread out and are densely packed. It uses fuzzy c-means (FCM) clustering to smartly pick the best forwarders based on how many nodes are nearby. By focusing on the sender’s immediate surroundings, FCM-OR helps solve the problems that arise when different parts of the network have varying densities of nodes. We also created a new way to measure routing effectiveness called “forwarding rank”. To test how well our protocol works, we ran extensive simulations comparing it to existing methods, including opportunistic routing with duty-cycled WSNs and load-balanced opportunistic routing. The results are clear: FCM-OR significantly improves both network performance and energy efficiency, especially in networks where nodes are not uniformly distributed.

ElectronicsVol. 14(9)
Chosun University (KR)
Chosun University
Openalex Percentile: Top 6%
Energy Efficient Wireless Sensor Networks
4.46
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