Low-Latency Low-Energy Adaptive Clustering Hierarchy Protocols for Underwater Acoustic Networks

Low-Latency Low-Energy Adaptive Clustering Hierarchy Protocols for Underwater Acoustic Networks

A. S. Ghazy, G. Kaddoum and S. Singh, “Low-Latency Low-Energy Adaptive Clustering Hierarchy Protocols for Underwater Acoustic Networks,” in IEEE Access, vol. 11, pp. 50578-50594, 2023, doi: 10.1109/ACCESS.2023.3277395.

Abstract or Summary

Underwater acoustic cluster networks (UACNs) are commonly used due to their adaptability in dynamic underwater environments. While the low-energy adaptive clustering hierarchy (LEACH) protocol was initially designed for radio frequency (RF) cluster networks, it has also been applied to UACNs. However, the LEACH protocol uses lengthy overheads per packet due to its use of global or wide-scale IDs, leading to increased communication latency and energy usage per packet. To address this issue, we propose the low-latency low-energy adaptive clustering hierarchy (L3EACH) protocol. The L3EACH protocol is a comprehensive framework that integrates ID assignment, time slot reservation, packet routing, and self-network organization. The protocol uses shorter overheads by assigning local IDs instead of global or widescale IDs. It assigns unique IDs to nodes within a cluster and reassigns the same IDs to nodes in other clusters, i.e., spatial ID reuse. The protocol also allocates IDs and time slots on demand to maximize network resources. To further enhance the protocol, we introduce the L3EACH-Version 2 (L3EACH-V2) protocol, which modulates the preamble bits to embed the IDs in the overhead rather than inserting extra bits. We also provide the computational complexity of the L3EACH-V2 protocol. Compared to the DIVE protocol, the L3EACH protocol reduces the ID length and average energy per packet by 50% and 13%, respectively. Furthermore, the L3EACH-V2 protocol reduces the average energy per packet by 27% and increases the network throughput by 16% compared to the L3EACH protocol, making it an efficient and scalable solution, especially, for dense UACNs.

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