Optimization of Manets Using Aomdv With Novel Aging Multi Population Strategy for Effectual Energy Utilization

Abstract

In today’s world wireless technologies plays vital role for many real world applications particularly the Mobile Ad-hoc Network (MANET) with bidirectional transmission capacity through numerous intermediary nodes is having dynamic scope in near future. Whereas, packet collision is regarded as the most important restrictions in MANETs since nodes move randomly through the network at unpredictable speeds, increasing the likelihood of collision and degrading throughput, routing overhead, and end-to-end delay. Additionally, a topological shift and link instability caused by frequent node mobility lower the rate of data delivery. The probability of traffic crowding increases at the intermediary nodes due to limited possible routes to the destination network, which affects the successful delivery of packets, especially with real-world applications on MANETs. In the proposed work, a novel strategy of age to evaluate each particle's local area search capacity is anticipated with Aging Multi Population Optimization (AMPO). The particles are divided into distinct age groups according to their ages so that population variety can be maintained when searching. Particles within every group of age can only choose those in younger or from their own clusters / groups as preferred neighbors. To choose the optimum route to the destination, we optimise the many pathways that the Adhoc On-demand Multipath Distance Vector (AOMDV) mechanism returned. The most ideal route is thought to be the one with the highest value for fitness. In order to speed up convergence, we also create a parameter setting mechanism based on age groups, where particles in various age groups have distinct parameters. Finally, we evaluate our suggested approach in comparison to AOMDV-TA and EHO-AOMDV. For the performance assessment of the suggested model, network overhead, throughput, delay, energy usage, and delivery of packets range as vital aspects.