LETTERS International Journal of Recent Trends in Engineering, Vol 2, No. 6, November 2009 80 Multi-objective Particle Swarm Optimization for Wireless video Support Yakubu Suleiman Baguda 1 , Norsheila Fisal 2 , and Dahiru Sani Shuaibu 3 1, 2, 3 Department of Optics & Communication Engineering, Faculty of Electrical Engineering University of Technology, Malaysia Johor, Malaysia. E-mail: {baguda_pg,sheila}@fke.utm.my Abstract—The need to achieve optimal performance is extremely important and significant while making more critical decision especially in time-varying channel condition. There has been increasing demand for highly efficient optimization scheme due to rapid growth and development in wireless multimedia systems. Delay has been a major issue which has detrimental impact on the performance of the wireless network and subsequently leads to incessant packet and congestion as well. In order to mitigate this problem, it is very important to have an efficient optimization technique which can perform complex task within the shortest possible time especially while dealing with delay sensitive applications. Therefore, we proposed multi-objective scheme using particle swarm optimization to effectively enhance the computational time which eventually support delay sensitive applications over wireless LAN. The scheme has shown that multi-objective PSO can significantly and conveniently satisfy the delay requirement for multimedia applications over wireless medium. Index Terms—Quality of service (QoS), particle swarm optimization (PSO), multi-objective optimization, optimal solution, Cross layer design I. INTRODUCTION There has been rapid increase in demand for optimization in order to achieve optimal performance in engineering, management and planning. This is due to dramatic need for efficient and economical design solution, allocating limited resources and planning industrial operations [1]. With rapid growth of optimization techniques in engineering, more complicated problems can be solve with relative ease and sophistication. More importantly, advancement in computing has contributed tremendously toward achieving more remarkable results with high precision and accuracy. Particle swarm optimization (PSO) [2][3] has been extremely important tool which dramatically reduce the processing time and complexity as well. PSO is a well known optimization technique which is based on social animal behavour. This is primarily due to its capability to converge rapidly, simplicity and searching capability. The aforementioned characteristics of PSO when fully exploited can play more significant role in minimizing the time required to make critical decision. More importantly, it will enhance the network robustness and flexibility as well. Wireless network requires more efficient scheme and strategy to increase the performance of the network. Hence, many parameters need to be considered and therefore multi-objective PSO is needed to properly manage conflicting objective functions. It can eventually happen in real life situation and therefore multi-objective PSO can effectively and efficiently provides the best optimal solution within the time limit for multimedia application. The ability to meet up with packet deadline is very important in delay sensitive application where any delay can seriously affect the multimedia content. The remainder of this paper is organized as follows. Section II mainly focuses on the overview of multi- objective PSO and the related work. Section III introduces our proposed scheme. Simulations results are presented in Section IV. Finally, conclusions are enumerated in Section V. II. OVERVIEW OF PSO In recent years, swarm intelligence has been used extensively in solving optimization problems and it primarily uses biologically inspired phenomenon. In fact, PSO has been very promising due to its fast convergence and simplicity. This can be applicable in supporting delay sensitive applications which require highly efficient and sophistication. It is very obvious that in order to enhance the performance of wireless multimedia applications, many parameters and factors should be considered. Hence, multi-objective optimization PSO can eventually solve variety of multi-objective problems to achieve optimal performance [4][5]. More importantly, multi-objective PSO can effectively search and determine the set of optimal solutions simultaneously [6][7]. The wireless channel characteristic can be represented by highly non- linear objective and constraint in order to genuinely consider its impact on the transmitted data or information. Particle swarm optimization mainly used stochastic optimization to mimic the natural phenomenon. It primarily produces a set of solution and further modified as the process continues. This has been very efficient and powerful tool for searching the optimal solution to a given particular problem. Problems dealing with multiple objective function can be solve using multi-objective PSO with relative ease and high searching capability for optimum solution. Due to aforementioned reasons, multi- objective PSO can be used in wireless network to enhance the performance of the © 2009 ACADEMY PUBLISHER