A novel data aggregation using multi objective based male lion optimization algorithm (DA-MOMLOA) in wireless sensor network

Abstract

Wireless sensor network efficiently aggregates and transmits data in an internet of things (IoT) environment. Machine Learning algorithms can minimize data transmission rates by utilizing the distributive features of the network. This study proposes a novel cluster-based data aggregation method using multi-objective based male lion optimization algorithm (DA-MOMLOA) for evaluating the network based on energy, delay, density and distance. The data aggregation method is employed with the help of cluster head wherein data aggregated from similar clusters are forwarded to the sink node following by application of machine learning algorithms. Hence, the proposed method shows promising results as it significantly increases the network efficiency and reduces the packet drop owing to a smaller number of aggregation processes.