Modeling and performance comparison of reliability strategies for distributed video servers
Large scale video servers are typically based on disk arrays that comprise multiple nodes and many hard disks. Due to the large number of components, disk arrays are susceptible to disk and node failures that can affect the server reliability. Therefore, fault tolerance must be already addressed in the design of the video server. For fault tolerance, we consider parity-based as well as mirroring-based techniques with various distribution granularities of the redundant data. We Identify several reliability schemes and compare them in terms of the server reliability and per stream cost. To compute the server reliability, we use continuous time Markov chains that are evaluated using the SHARPE software package. Our study covers independent disk failures and dependent component failures. We propose a new mirroring scheme called Grouped One-to-One scheme that achieves the highest reliability among all schemes considered. The results of this paper indicate that dividing the server into independent groups achieves the best compromise between the server reliability and the cost per stream. We further find that the smaller the group size, the better the trade-off between a high server reliability and a low per stream cost.
distributed video servers markov chains sharpe reliability modeling performance and cost analysis