Efficient Energy and Delay Reduction Model for Wireless Sensor Networks

Abstract

In every network, delay and energy are crucial for communication and network life. In wireless sensor networks, many tiny nodes create networks with high energy consumption and compute routes for better communication. Wireless Sensor Networks (WSN) is a very complex scenario to compute minimal delay with data aggregation and energy efficiency. In this research, we compute minimal delay and energy efficiency for improving the quality of service of any WSN. The proposed work is based on energy and distance parameters as taken dependent variables with data aggregation. Data aggregation performs on different models, namely Hybrid-Low Energy Adaptive Clustering Hierarchy (H-LEACH), Low Energy Adaptive Clustering Hierarchy (LEACH), and Multi-Aggregator-based Multi-Cast (MAMC). The main contribution of this research is to a reduction in delay and optimized energy solution, a novel hybrid model design in this research that ensures the quality of service in WSN. This model includes a whale optimization technique that involves heterogeneous functions and performs optimization to reach optimized results. For cluster head selection, Stable Election Protocol (SEP) protocol is used and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) is used for driven-path in routing. Simulation results evaluate that H-LEACH provides minimal delay and energy consumption by sensor nodes. In the comparison of existing theories and our proposed method, H-LEACH is providing energy and delay reduction and improvement in quality of service. MATLAB 2019 is used for simulation work.