Underwater Acoustic Sensor Node Scheduling And Energy Efficient Routing Problem Using Evolutionary Algorithms

Abstract

Underwater Acoustic Sensor Networks (UWASNs) is becoming a great research newlinetopic for several researchers, which plays a significant role in monitoring the aqueous newlineenvironment. Several applications like offshore exploration, pollution monitoring, disaster newlineprevention, oceanographic data collection, tactical surveillance, and assisted navigation newlineapplications are applicable using UWASN. One of UWASNs primary constraints newlineis the restricted energy since nodes are battery powered and are active in the deep ocean newlineenvironment. In such networks, it is not feasible to frequently recharge or replace batteries newlinethat make energy efficiency a significant metric in UWASN. In an effective UWASN newlineexecution, the technical task is to create efficient use of limited available acoustic channel newlinebandwidth. One way to solve this challenge is broadcast scheduling of channel newlineusage by way of time division multiple access (TDMA). The basic idea is to address the newlinebroadcast scheduling problem in UWASN for utilizing the limited available bandwidth newlineby parallelizing the node transmission such that it does not interfere with each other in newlinethe same time slot. Besides minimizing the node turnaround transmission time in the newlinenetwork by optimizing the time frame in the TDMA using evolutionary algorithms. For newlinethe effective stream of data from origin to destinations, the routing protocol performs a newlinesignificant part in UWASNs. In this research study using an evolutionary algorithm, the newlinevector-based forwarding (VBF) routing path is divided into route cover set to minimize newlinethe energy consumption. newlineThe research work includes the following contributions: (1) To identify an efficient newlinebroadcast TDMA schedule with minimum length TDMA frame for subsequent node newlineturn around transmission and maximum acoustic channel utilization in reduced computation newlinetime using multi-objective evolutionary algorithms and (2) To solve the minimum newlineenergy VBF routing path over UWASNs in less computation time using memetic flower newlinepollination algorithm. newline