Fault-Tolerant Backup Clustering Algorithm for Smart Connected Underwater Sensor Networks
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This paper addresses poor cluster formation and frequent Cluster Head (CH) failure issues of underwater sensor networks by proposing an energy-efficient hierarchical topology-aware clustering routing (EEHTAC) protocol. In this paper, fault-tolerant backup clustering (FTBC) algorithms and multi-parameter cluster formation (MPCF) model were developed for the EEHTAC operation. The MPCF model tackles the issue of poor cluster formation performance by integrating multiple parameters to achieve effective clustering process. The FTBC algorithms tackle the issue of frequent CH failures to avoid interruption in data transmission. Performance of the MPCF model was evaluated using normal, high-fault, and high routing overhead network scenarios. Performance metrics employed for this analysis are temporal topology variation ratio (TTVR), CH load distribution (CLD), and cluster stability (STB). Obtained results show that operating with a CH retention period of 90s achieves better CH duty cycling per round and improves the MPCF process with values of 25.69 and 60 EEHTAC was evaluated relative to Energy-balanced Unequal Layering Clustering (EULC) protocol. Performance indicators adopted for this evaluation are routing overhead (Ω), end to end delay (Δ), CH failures recovered (CFR), CH failures detected (CFD), received packets (θ), and energy consumption (Σ). With reference to the best obtained values, EEHTAC demonstrated performance improvement of 58.40 over EULC variants in terms of Ω, Δ, CFR, CFD, θ, and Σ respectively. Obtained results displayed that the MPCF model is efficient for cluster formation performance and the FTBC-based EEHTAC protocol can perform effectively well against an existing CBR protocol.
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