This Article 
 Bibliographic References 
 Add to: 
Load Balancing in a Cluster-Based Web Server for Multimedia Applications
November 2006 (vol. 17 no. 11)
pp. 1321-1334

Abstract—We consider a cluster-based multimedia Web server that dynamically generates video units to satisfy the bit rate and bandwidth requirements of a variety of clients. The media server partitions the job into several tasks and schedules them on the backend computing nodes for processing. For stream-based applications, the main design criteria of the scheduling are to minimize the total processing time and maintain the order of media units for each outgoing stream. In this paper, we first design, implement, and evaluate three scheduling algorithms, First Fit (FF), Stream-based Mapping (SM), and Adaptive Load Sharing (ALS), for multimedia transcoding in a cluster environment. We determined that it is necessary to predict the CPU load for each multimedia task and schedule them accordingly due to the variability of the individual jobs/tasks. We, therefore, propose an online prediction algorithm that can dynamically predict the processing time per individual task (media unit). We then propose two new load scheduling algorithms, namely, Prediction-based Least Load First (P-LLF) and Prediction-based Adaptive Partitioning (P-AP), which can use prediction to improve the performance. The performance of the system is evaluated in terms of system throughput, out-of-order rate of outgoing media streams, and load balancing overhead through real measurements using a cluster of computers. The performance of the new load balancing algorithms is compared with all other load balancing schemes to show that P-AP greatly reduces the delay jitter and achieves high throughput for a variety of workloads in a heterogeneous cluster. It strikes a good balance between the throughput and output order of the processed media units.

[1] S. Chandra, C.S. Ellis, and A. Vahdat, “Differentiated Multimedia Web Services Using Quality Aware Transcoding,” Proc. INFOCOM 2000-19th Ann. Joint Conf. IEEE Computer and Comm. Soc., Mar. 2000.
[2] R. Keller, S. Choi, M. Dasen, D. Decasper, G. Fankhauser, and B. Platter, “An Active Router Architecture for Multicast Video Distribution,” Proc. IEEE INFOCOM, 2000.
[3] G. Welling, M. Ott, and S. Mathur, “A Cluster-Based Active Router Architecture,” IEEE Micro, vol. 21, no. 1, Jan./Feb. 2001.
[4] M. Ott, G. Welling, S. Mathur, D. Reininger, and R. Izmailov, “The Journey Active Network Model,” IEEE J. Selected Areas in Comm., vol. 19, no. 3, pp. 527-537, Mar. 2001.
[5] A. Fox, S. Gribble, E. Brewer, and E. Amir, “Adapting to Network and Client Variability via On-Demand Dynamic Distillation,” Proc. Seventh Int'l Conf. Architecture Support for Programming Language and Operating Systems (ASPLOS-VII), 1996.
[6] A. Fox, S.D. Gribble, and Y. Chawathe, “Adapting to Network and Client Variation Using Active Proxies: Lessons and Perspectives,” IEEE Personal Comm. on Adaptation, special issue, 1998.
[7] E. Amir, S. McCanne, and R. Katz, “An Active Service Framework and Its Application to Real-Time Multimedia Transcoding,” Proc. ACM SIGCOMM Symp., Sept. 1998.
[8] B.A. Shirazi, A.R. Hurson, and K.M. Kavi, Scheduling and Load Balancing in Parallel and Distributed Systems. CS Press, 1995.
[9] M. Satyanarayanan, “Scalable, Secure, and Highly Available Distributed File Access,” Computer, May 1990.
[10] E. Katz, M. Butler, and R. McGrath, “A Scalable Http Server: The Ncsa Prototype,” Computer Networks and ISDN Systems, vol. 27, pp.155-164, 1994.
[11] H. Zhu, T. Yang, Q. Zheng, D. Watson, O. Ibarra, and T. Smith, “Adaptive Load Sharing for Clustered Digital Library Servers,” Proc. Seventh Int'l Symp. High Performance Distributed Computing, pp. 235-242, 1998.
[12] H. Zhu, H. Tang, and T. Yang, “Demand-Driven Service Differentiation in Cluster-Based Network Servers,” Proc. IEEE INFOCOM, 2001.
[13] C. Li, G. Peng, K. Gopalan, and T. Chiueh, “Performance Garantees for Cluster-Based Internet Services,” Proc. 23rd Int'l Conf. Distributed Computing Systems (ICDCS '03), May 2003.
[14] J. Guo, F. Chen, L. Bhuyan, and R. Kumar, “A Cluster-Based Active Router Architecture Supporting Video/Audio Stream Transcoding Services,” Proc. 17th Int'l Parallel and Distributed Processing Symp. (IPDPS '03), Apr. 2003.
[15] L. Kencl and J.Y.L. Boudec, “Adaptive Load Sharing for Network Processors,” Proc. IEEE INFOCOM, 2002.
[16] A.D. Bavier, A.B. Montz, and L.L. Peterson, “Predicting Mpeg Execution Times,” Proc. Int'l Conf. Measurements and Modeling of Computer Systems (SIGMETRICS), pp. 131-140, 1998.
[17] Ffmpeg Multimedia System, http:/, 2004.
[18] C.K. Hess, D. Raila, R.H. Campbell, and D. Mickunas, “Design and Performance of MPEG Video Streaming to Palmtop Computers,” Multimedia Computing Networks, 2000.
[19] E. Amir, S. McCanne, and H. Zhang, “An Application Level Video Gateway,” Proc. ACM Multimedia, 1995.
[20] A. Fox, S.D. Gribble, Y. Chawathe, E.A. Brewer, and P. Gauthier, “Cluster-Based Scalable Network Services,” Proc. Symp. Operating Systems Principles, 1997.
[21] K.W. Ross, “Hash Routing for Collections of Shared Web Caches,” IEEE Network, vol. 11, no. 6, Nov.-Dec. 1997.
[22] Y. He, I. Ahmad, and M.L. Liou, “Real-Time Interactive MPEG-4 System Encoder Using a Cluster of Workstations,” IEEE Trans. Multimedia, vol. 1, no. 2, pp. 217-233, 1999.

Index Terms:
Online prediction, partial predictor, global predictor, adaptive partioning, prediction-based load balancing, out-of-order rate.
Jiani Guo, Laxmi Narayan Bhuyan, "Load Balancing in a Cluster-Based Web Server for Multimedia Applications," IEEE Transactions on Parallel and Distributed Systems, vol. 17, no. 11, pp. 1321-1334, Nov. 2006, doi:10.1109/TPDS.2006.159
Usage of this product signifies your acceptance of the Terms of Use.