STATISTICAL MARKOV MODEL BASED NATURAL INSPIRED GLOWWORM SWARM MULTI-OBJECTIVE OPTIMIZATION FOR ENERGY EFFICIENT DATA DELIVERY IN MANET

Thiyagarajan Perumal

doi:10.5755/j01.itc.49.2.23554

Abstract

An interference and collision is a significant problem to be solved in Mobile Ad Hoc Network (MANET). Few techniques were developed in existing work to perform energy aware routing in MANET. But, handling both interference and collision on route path was remained open issues which increases the energy usage and reduces the throughput of MANET. In order to overcome such limitations, Statistical Markov Model Based Natural Inspired Glowworm Multi-objective Optimization (SMM-NIGMO) technique is proposed. The SMM-NIGMO technique contains three key processes namely interference prediction, optimal node selection, route path identification. The SMM-NIGMO technique at first proposes a Statistical Markov Model to determine the interference level of each mobile node in MANET at the time ‘ ’. After that, SMM-NIGMO Technique designs a Natural Inspired Glowworm Swarm Multi-Objective Optimization (NIGSMO) algorithm to carry out the optimal node selection process in MANET. During this process, SMM-NIGMO Technique finds the mobile nodes with lower inferences and higher residual energy as optimal in dynamic environment. After discovering the best nodes, SMM-NIGMO Technique uses the Request-To-Send (RTS) and Clear-To-Send (CTS) mechanism for identifying the best route path in MANET. During the route path finding process, SMM-NIGMO Technique selects the mobile node to transmit the packets to destination without any collisions. As a result, SMM-NIGMO Technique enhances the performance of energy efficient data delivery in MANET as compared to existing works. The simulation of SMM-NIGMO Technique is performed using parameters such as throughput, energy consumption, packet loss rate and end to end delay. The simulation result depicts that the SMM-NIGMO Technique is able to improve the throughput and also reduces the energy consumption of data transmission in MANET as compared to state-of-the-art works.

Highlights

A Mobile Ad Hoc Network (MANET) includes a set of mobile nodes that move freely and self-configure without an infrastructure
The SMMNIGMO technique is introduced by integrating the Statistical Markov Model and Natural Inspired Glowworm Swarm Multi-Objective Optimization (NIGSMO) algorithm and Request-To-Send (RTS) and Clear-To-Send (CTS) mechanism. _ To minimize the interference level on route path through finding the optimal mobile nodes in MANET and thereby increasing throughput and reducing energy usage as compared to existing works, Statistical Markov Model and Natural Inspired Glowworm Swarm Multi-Objective Optimization (NIGSMO) algorithm are designed in SMM-NIGMO technique. _ To reduce the occurrence of collision during data transmission and thereby minimizing the packet loss rate and an End-to-End delay as compared to state-of-the-art works, Request-To-Send (RTS) and Clear-To-Send (CTS) mechanism is employed in SMM-NIGMO technique
Our Proposed Statistical Markov Model Based Natural Inspired Glowworm Multi-objective Optimization (SMM-NIGMO) techniques provides a different approach for deliberately selecting optimal node selection for finding route path and attain energy efficient data transmission in MANET

Summary

Introduction

A Mobile Ad Hoc Network (MANET) includes a set of mobile nodes that move freely and self-configure without an infrastructure. The above two existing methods not consider any algorithm for collision avoidance To solve these drawbacks, SMM-NIGMO technique is introduced in this work. _ To improve the performance of energy efficient data delivery via an interference and collision reduction in MANET as compared to conventional works, SMM-NIGMO technique is developed. _ To minimize the interference level on route path through finding the optimal mobile nodes in MANET and thereby increasing throughput and reducing energy usage as compared to existing works, Statistical Markov Model and Natural Inspired Glowworm Swarm Multi-Objective Optimization (NIGSMO) algorithm are designed in SMM-NIGMO technique. _ To reduce the occurrence of collision during data transmission and thereby minimizing the packet loss rate and an End-to-End delay as compared to state-of-the-art works, Request-To-Send (RTS) and Clear-To-Send (CTS) mechanism is employed in SMM-NIGMO technique.

Related Works

Motivation

Simulation Settings

Result and Discussions

Performance Measure of Mobility Strategies

Conclusion