Performance analysis of server selection schemes for
Video on Demand servers

Dash, Suraj and Prusty, Alok Kumar (2011) Performance analysis of server selection schemes for
Video on Demand servers.
BTech thesis.



Web Services have gained considerable attention over the last few years. This is due to increase in use of the Internet which results in increased web traffic. Web servers find applications in E-commerce and Video-on-Demand(VoD) systems which have resulted in speedy growth of the web traffic. Therefore the concept of load balancer aimed to distribute the tasks to different Web Servers to reduce response times was introduced. Each request was assigned a Web Server decided by the load balancer in such a way that tasks were uniformly distributed among the available servers. Server selection algorithms are
aimed to meet the QoS for interactive VoD.This thesis attempts to analyze the performance of FCFS, Randomized, Genetic algorithms and Heuristics algorithms for selecting
server to meet the VoD requirement . Performance of these algorithms have been simulated with parameters like makespan and average resource utilization for different server models. This thesis presents an efficient heuristic called Ga-max-min for distributing the load among different servers. Heuristics like min-min and max-min are also applied to heterogeneous server farms and the result is compared with the proposed heuristic for VoD Servers. Ga-max-min was found to provide lower makespan and higher resource utilization than the genetic algorithm.Extensive simulations have been carried out by the simulator designed using MATLAB R2010a.

Item Type:Thesis (BTech)
Uncontrolled Keywords:makespan,resource utilization,VoD,Genetic Algorithm,Max-min,Min-min
Subjects:Engineering and Technology > Computer and Information Science > Networks
Divisions: Engineering and Technology > Department of Computer Science
ID Code:2667
Deposited By:Mr. Alok Kumar Prusty
Deposited On:19 May 2011 21:33
Last Modified:19 May 2011 21:33
Supervisor(s):Sahoo, B D

Repository Staff Only: item control page