Fast concurrent access to parallel disks
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Random duplicate storage strategies for load balancing in multimedia servers
Information Processing Letters
Exploring Content Delivery Networking
IT Professional
COMPCON '96 Proceedings of the 41st IEEE International Computer Conference
Video server on an ATM connected cluster of workstations
SCCC '97 Proceedings of the 17th International Conference of the Chilean Computer Science Society
Optimal Video Replication and Placement on a Cluster of Video-on-Demand Servers
ICPP '02 Proceedings of the 2002 International Conference on Parallel Processing
Analyzing client interactivity in streaming media
Proceedings of the 13th international conference on World Wide Web
A survey of peer-to-peer content distribution technologies
ACM Computing Surveys (CSUR)
A Novel Realistic Simulation Tool for Video Transmission over Wireless Network
SUTC '06 Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing -Vol 1 (SUTC'06) - Volume 01
Designing a Video-on-Demand System for a Brazilian High Speed Network
ICDCSW '06 Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems
Digital video cluster simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Understanding user behavior in large-scale video-on-demand systems
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
A survey and comparison of peer-to-peer overlay network schemes
IEEE Communications Surveys & Tutorials
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The optimization of Clustered Streaming Media Servers (CSMS), which aims at using as few hardware resources and as cost-effective as possible, while providing satisfactory performance and QoS, has a great impact on the practicability and efficiency of CSMS. Based on the analysis and formulization of critical performance factors of CSMS and the relationship among the performance, QoS, and the costs in CSMS, a stepwise optimization algorithm is developed to solve the optimization problem efficiently. The algorithm is based on an approach that models the optimization problem into a directed acyclic graph and then addresses the complex optimization problem step by step. The algorithm applies a divide and conquer model that not only reduces the complexity of the optimization problem, but also accelerates the optimization process. Progressive information is collected in the process and used in solving the problem. Furthermore, a simulation system of CSMS is necessary for the optimization algorithm to generate the accurate information produced in the entire streaming service process. Thus, we designed and implemented such a simulation system based on the theoretical performance model of CSMS and the parameters measured in practical CSMS testbed. Finally, a case study of the optimization problem is given to demonstrate the process of the algorithm, and an appropriate plan for designing practical CSMS system is illustrated.