Optimized AODV Routing Algorithm in MANET for Maximizing the Network Lifetime

Abstract

In present scenario, Mobile Ad-hoc Networks (MANETs) is the emerging research topic in the applications like disaster situations (battle fields, earthquake, etc). The utility of MANET is increased by combining with the internet. The conventional techniques in MANET have a few issues like less infrastructure, standalone networks, and dynamic or complex topology. In order to address these issues, an efficient clustering and channeling algorithm (Hybrid K-means, Particle Swarm Optimization (PSO) based Ad-hoc On-demand Distance Vector (AODV) channeling algorithm) is developed for maximizing the network lifetime. The proposed algorithm finds the optimal cluster head selection for discovering the shortest path among the cluster heads. The Hybrid-K-means-PSO-AODV technique is applied to increase the Network Lifetime (NL), alive nodes, total packet send, throughput, and also to minimizes the dead nodes and energy consumption in a network. In the experimental phase, the proposed approach reduced the emery consumption up to 170 joules related to the existing approaches: PSO-PSO- MANETs and PSO-GSO- MANETs.

Cost Optimization Approach for MANET using Particle Swarm Optimization

“…It describe the way of finding children of a node in order to find out shortest path that is useful to have maximum life of a node. Proposed link life prediction algorithm find out life of a node so that path can be created using maximum life of a node so transmission can be done for maximum amount of time [11]. It is advisable to use power optimized cross layer design based protocol for reduction of loss of energy and boost the life of the network for long duration data transmission [12].…”

“…Given equation is used to find out best speed and location of the particle in the search space [11].…”

Optimasisasi Mobile Ad-Hoc Network dengan Algoritma Particle Swarm Optimization

“…Berdasarkan penelitian terdahulu pada formasi burung nilai end to end delay protokol routing AOMDV lebih besar jika dibandingkan dengan protokol routing AODV seiring dengan bertambahnya jumlah node yang digunakan dalam simulasi. Hal ini dikarenakan routing DSR mengalami proses pencarian jalur lebih lama dan lebih panjang dibanding AODV [4]. Hal ini mengakibatkan rata-rata delay pada routing DSR lebih lama karena banyaknya hop yang ditempuh dari node sumber ke node tujuan.…”

“…Pergerakan node merupakan pergerakan dari node pada saat simulasi dijalankan. Untuk penilitian ini pergerakan node yang digunakan yaitu rand\om waypoint model dan manhattan mobility model [4]. Dalam pergerakan random Dibawah ini adalah contoh pembuatan pergerakan node.…”