FLCEER: Fuzzy Logic Cluster-Based Energy Efficient Routing Protocol for Underwater Acoustic Sensor Network

Sathishkumar Natesan and Rajakumar Krishnan
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Sathishkumar Natesan: School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India
Rajakumar Krishnan: School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

International Journal of Information Technology and Web Engineering (IJITWE), 2020, vol. 15, issue 3, 76-101

Abstract: Underwater acoustic sensor networks (UASN) play a crucial role in various applications such as tsunami detection, surveillance of the ocean by the defense department, monitoring offshore oil, and identifying gas basins underwater. UASNs can be one of the supporting infrastructures for the Internet of Things (IoT). UASNs have the problems of long latency, high bit error rate, and low bandwidth. These pose various challenges such as high consumption of energy, low reliability, low packet retransmission, and high delay for UASNs. To overcome the shortcomings mentioned above, various approaches are suggested. This article proposes a multi-layer fuzzy logic cluster-based energy-efficient routing protocol for UASNs. It splits the network area into equal sized rings. The priority number (PRN) is utilized for all underwater cluster heads (UCHs). Based on the highest PRN, the UCH starts communicating among UCHs. Here, the PRN makes the task very selective avoiding collisions and also reducing propagation delays. The cluster formation is done by sending a message to all underwater cluster members (UCMs) and the selection of UCH and UCM are done. Each has a threshold value. The intra-ring clustering process splits a ring into equal-sized clusters. Additionally, inter-cluster routing applies the fuzzy logic metrics to choose the optimum data route in transferring the data from the underwater cluster head (UCH) to the sink node (SN). It is tested using Aqua-Sim simulation which is based on NS2. It is compared with an existing protocol such as multi-layer cluster energy efficient (MLCEE), depth-based routing (DBR), energy efficient DBR (EEDBR). The results prove that it has improved energy efficiency, packet delivery ratio, throughput, and the network's lifetime.

Date: 2020
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