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http://hdl.handle.net/2080/2013
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DC Field | Value | Language |
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dc.contributor.author | Prusty, A K | - |
dc.contributor.author | Sahoo, Bibhudatta | - |
dc.date.accessioned | 2013-10-01T10:02:33Z | - |
dc.date.available | 2013-10-01T10:02:33Z | - |
dc.date.issued | 2013-08 | - |
dc.identifier.citation | CiiT International Journal of Artificial Intelligent Systems and Machine Learning, Vol.5, No.8 August -2013 | en |
dc.identifier.uri | http://hdl.handle.net/2080/2013 | - |
dc.description | Copyright belongs to proceeding publisher | en |
dc.description.abstract | The Web Services have gained considerable attention over the last few years. Video-on-Demand (VoD) systems 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. This paper attempts to analyze the performance of FCFS, Randomized, Genetic algorithms and Heuristics algorithms for selecting server to meet the VoD requirement. Performances of these algorithms have been simulated with parameters like makespan and average resource utilization for different server models. This paper presents an efficient heuristic called Ga-max-min for distributing the load among 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. | en |
dc.format.extent | 153408 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.publisher | Coimbatore Institute of Information Technology | en |
dc.subject | Makespan | en |
dc.subject | Resource Utilization | en |
dc.subject | FCFS | en |
dc.subject | Random | en |
dc.subject | Genetic | en |
dc.subject | Max-min | en |
dc.subject | Min-min | en |
dc.title | Heuristics Load Balancing Algorithms for Video on Demand Servers | en |
dc.type | Article | en |
Appears in Collections: | Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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HLBA_Vod_nitr.pdf | 149.81 kB | Adobe PDF | View/Open |
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