Maximizing the availability and reliability of videos in VoD system using markov chain

R. Ashok Kumar; K. Hareesh; K. Ganesan; D. H. Manjaiah

doi:10.1109/CTRQ.2009.16

Maximizing the availability and reliability of videos in VoD system using markov chain

R. Ashok Kumar, K. Hareesh, K. Ganesan, D. H. Manjaiah

Department of Computer Applications, Manipal Institute of Technology, Manipal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

In a Video on Demand system, by forwarding the server video stream client by client, a chain based scheme is formed, which reduces the server load. The existing chaining schemes are not reliable because there are frequent breaks in the chain among the clients due to stringent bandwidth and buffer, stop fail, and hardware and software failures. This leads to stream failures within the client, in turn affects other clients in the cluster. Then, the performance of the overall system degrades. To achieve system reliability we formulated a Continuous Time Markov Chain reliability model and analyzed the availability and reliability of the streams during the intricate circumstances. Numerical results show that for 5000 streams, we obtain the reliability between 60% and 80%, even though the individual clients are highly unreliable.

Original language	English
Title of host publication	2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009
Pages	15-19
Number of pages	5
DOIs	https://doi.org/10.1109/CTRQ.2009.16
Publication status	Published - 12-11-2009
Event	2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009 - Colmar, France Duration: 20-07-2009 → 25-07-2009

Conference

Conference	2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009
Country	France
City	Colmar
Period	20-07-09 → 25-07-09

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All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Signal Processing
Software
Safety, Risk, Reliability and Quality

Cite this

Kumar, R. A., Hareesh, K., Ganesan, K., & Manjaiah, D. H. (2009). Maximizing the availability and reliability of videos in VoD system using markov chain. In 2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009 (pp. 15-19). [5176062] https://doi.org/10.1109/CTRQ.2009.16

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abstract = "In a Video on Demand system, by forwarding the server video stream client by client, a chain based scheme is formed, which reduces the server load. The existing chaining schemes are not reliable because there are frequent breaks in the chain among the clients due to stringent bandwidth and buffer, stop fail, and hardware and software failures. This leads to stream failures within the client, in turn affects other clients in the cluster. Then, the performance of the overall system degrades. To achieve system reliability we formulated a Continuous Time Markov Chain reliability model and analyzed the availability and reliability of the streams during the intricate circumstances. Numerical results show that for 5000 streams, we obtain the reliability between 60{\%} and 80{\%}, even though the individual clients are highly unreliable.",

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Kumar, RA, Hareesh, K, Ganesan, K & Manjaiah, DH 2009, Maximizing the availability and reliability of videos in VoD system using markov chain. in 2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009., 5176062, pp. 15-19, 2009 2nd International Conference on Communication Theory, Reliability, and Quality of Service, CTRQ 2009, Colmar, France, 20-07-09. https://doi.org/10.1109/CTRQ.2009.16

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AB - In a Video on Demand system, by forwarding the server video stream client by client, a chain based scheme is formed, which reduces the server load. The existing chaining schemes are not reliable because there are frequent breaks in the chain among the clients due to stringent bandwidth and buffer, stop fail, and hardware and software failures. This leads to stream failures within the client, in turn affects other clients in the cluster. Then, the performance of the overall system degrades. To achieve system reliability we formulated a Continuous Time Markov Chain reliability model and analyzed the availability and reliability of the streams during the intricate circumstances. Numerical results show that for 5000 streams, we obtain the reliability between 60% and 80%, even though the individual clients are highly unreliable.

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Access to Document

10.1109/CTRQ.2009.16