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Abstract
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Article Information:
Performance Evaluation of OLSR Using Swarm Intelligence and Hybrid Particle Swarm Optimization Using Gravitational Search Algorithm
S. Meenakshi Sundaram, A. Ramesh Babu and S. Palani
Corresponding Author: S. Meenakshi Sundaram
Submitted: October 09, 2013
Accepted: November 16, 2013
Published: April 19, 2014 |
Abstract:
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The aim of this research is to evaluate the performance of OLSR using swarm intelligence and HPSO with Gravitational search algorithm to lower the jitter time, data drop and end to end delay and improve the network throughput. Simulation was carried out for multimedia traffic and video streamed network traffic using OPNET Simulator. Routing is exchanging of information from one host to another in a network. Routing forwards packets to destination using an efficient path. Path efficiency is measured through metrics like hop number, traffic and security. Each host node acts as a specialized router in Ad-hoc networks. A table driven proactive routing protocol Optimized Link State Protocol (OLSR) has available topology information and routes. OLSR’s efficiency depends on Multipoint relay selection. Various studies were conducted to decrease control traffic overheads through modification of existing OLSR routing protocol and traffic shaping based on packet priority. This study proposes a modification of OLSR using swarm intelligence, Hybrid Particle Swarm Optimization (HPSO) using Gravitational Search Algorithm (GSA) and evaluation of performance of jitter, end to end delay, data drop and throughput. Simulation was carried out to investigate the proposed method for the network’s multimedia traffic.
Key words: Ad hoc network, gravitational search algorithm, Hybrid Particle Swarm Optimization (HPSO), multimedia traffic, Optimized Link State Routing (OLSR), ,
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Cite this Reference:
S. Meenakshi Sundaram, A. Ramesh Babu and S. Palani, . Performance Evaluation of OLSR Using Swarm Intelligence and Hybrid Particle Swarm Optimization Using Gravitational Search Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (15): 3126-3133.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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