An Effective Heuristics Approach for Performance Enhancement of MANET

Mobile Ad-hoc Networks (MANET) are widely adopted in almost all research fields due to their significant advantages like minimal energy consumption and compact size. In MANET major challenges are optimal coverage, a lifetime of nodes, and throughput. This paper proposed a hybrid ant colony-flower pollination (HAC - FP) algorithm for throughput maximization and minimal energy consumption in a sensor network. To enhance the performance of the MANET network this research adopts the meta-heuristic technique. The meta-heuristic approach utilized for the MANET network is the ant colony and flower pollination algorithm. The planned HAC-FP makes use of neighborhood distance to determine the best position for each node. With hypersphere localization, the Levy struggle in flower pollination is used for optimal energy location. The placement of sensor nodes is identified in the first step using a hypersphere. Sensor network node energy consumption is lowered based on neighborhood distance. The results showed that the suggested HAC-FP algorithm, rather than existing methodologies, enhances the MANET network's coverage area. Further proposed HAC-FP algorithm minimizes the energy consumption level of the MANET than the conventional genetic approach.