Load Distribution Strategies in Cluster-Based Transcoding Servers for Mobile Clients
The recent advance in wireless network technologies has enabled the streaming media service on the mobile devices such as PDAs and cellular phones. Since the wireless network has low bandwidth channels and mobile devices are actually composed of limited hardware specifications, the transcoding technology is needed to adapt streaming media to the given mobile devices. When large scale mobile clients demand the streaming service, load distribution strategies among transcoding servers highly impact on the total number of QoS streams. In this paper, the resource weighted load distribution strategy is proposed for the fair load balancing and the more scalable performance in cluster-based transcoding servers. Our proposed strategy is based on the weight of resources consumed for transcoding to classified client grades and the maximum number of QoS streams actually measured in transcoding servers. The proposed policy is implemented on cluster-based transcoding system. In experiments, we evaluate its fair load distribution and scalable performance according to the increase of transcoding servers.
KeywordsMobile Device Admission Control Load Distribution Mobile Client Client Request
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- 1.Sitaram, D., Dan, A.: Multimedia Servers: Applications, Environments, and Design. Morgan Kaufmann Publishers, San Francisco (2000)Google Scholar
- 2.Feng, W.C., Lie, M.: Critical Bandwidth Allocation Techniques for Stored Video Delivery Across Best-Effort Networks. In: The 20th International Conference on Distributed Computing Systems, pp. 201–207 (2000)Google Scholar
- 3.Du, D.H.C., Lee, Y.J.: Scalable Server and Storage Architectures for Video Streaming. In: IEEE International Conference on Multimedia Computing and Systems, pp. 191–206 (1999)Google Scholar
- 5.Li, C., Peng, G., Gopalan, K., Chiueh, T.: Performance guarantees for cluster-based internet services. In: Proceedings of the 23rd International Conference on Distributed Computing Systems, May 2003, pp. 378–385 (2003)Google Scholar
- 6.Roy, S., Covell, M., Ankcorn, J., Wee, S.: A System Architecture for Managing Mobile Streaming Media Services. In: 23rd International Conference on Distributed Computing Systems Workshops (ICDCSW 2003), pp. 408–419 (2003)Google Scholar
- 7.Guo, J., Chen, F., Bhuyan, L., Kumar, R.: A cluster-based active router architecture supporting video/audio stream transcoding services. In: Proceedings of the 17th International Parallel and Distributed Processing Symposium, April 2003, pp. 446–453 (2003)Google Scholar
- 9.Hess, C.K., Raila, D., Cambell, R.H., Mickunas, D.: Design and performance of mpeg video streaming to palmtop computers. In: Proceedings of SPIE/ACM Multimedia Computing and Networking (MMCN 2000) (January 2000)Google Scholar
- 10.Schmidt, B.K., Lam, M.S., Duane Northcutt, J.: The interactive performance of SLIM: a state-less, thin-client architecture. In: ACM SOSP 1999, pp. 31–47 (1999)Google Scholar
- 11.Aggarwal, C.C., Wolf, J.L., Yu, P.S.: On optimal batching policies for viedo-on-demand storage servers. In: Proc. of IEEE ICMCS 1996, Hiroshima, Japan, June 1996, pp. 253–258 (1996)Google Scholar
- 12.Chandra, S., Ellis, C.S., Vahdat, A.: Differentiated Multimedia Web Services Using Quality Aware Transcoding. In: Proceedings of IEEE INFOCOM Conference (March 2000)Google Scholar