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Enhancing Network Reliability in UASNs: A Collision-Aware Critical Node Identification Algorithm
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DOI：10.1109/TMC.2025.3600460.png)
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摘要
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Critical node identification is essential for Underwater Acoustic Sensor Networks (UASNs) to ensure network connectivity and reliability. Existing methods identify critical nodes by evaluating their contributions to network connectivity and node communication count. However, these methods identify critical nodes inaccurately due to neglecting the influence of packet collisions, leading to unreliable network. Packet collisions disrupt connected links and cause communication failures, resulting in unreliable network connectivity and improper communication count. To this end, we propose the Collision-Aware Critical Node Identification Algorithm (CCNIA), which accounts for the impact of packet collisions to improve the accuracy of critical node identification and enhance network reliability. CCNIA identifies critical nodes with high connectivity, large collision probability, and heavy network load, through building the three following interdependent models. Specifically, Topological Connectivity Model (TCM) evaluates link reachability by analyzing connectivity and density within a node's local network. Based on TCM, Collision Probability Model (CPM) further ensures packet reliability by quantifying the impact of packet collisions on critical node identification. Through CPM's reliable packet transmissions, Network Load Model (NLM) assesses network efficiency by analyzing node occurrence count within global end-to-end communication paths. Experiments show that CCNIA outperforms existing methods across diverse network configurations, enhancing network reliability in terms of packet delivery ratio, delay, and energy efficiency.
Keyword:
Reliability
Computer network reliability
Load modeling
Accuracy
Telecommunication traffic
Training
Reliability engineering
Mobile computing
Energy efficiency
Data mining
Collision probability
critical node identification
reliability
underwater acoustic sensor networks (UASNs)
期刊
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9.2
论文数:
5.9K
被引数:
1.8W
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引用论文
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Xu, C.; Song, S.; Liu, J.; Pan, M.; Xu, G.; Cui, J.H. Joint Power Control and Multipath Routing for Internet of Underwater Things in Varying Environments. IEEE Internet Things J. 2025, 12, 15197–15210. [Google Scholar] [CrossRef]徐, C.; 宋, S.; 刘, J.; 潘M.; 徐, G.; 崔J.H. 针对变化环境下的水下物联网联合功率控制与多路径路由。IEEE 物联网杂志. 2025, 12, 15197–15210. [Google Scholar] [CrossRef].png)
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