Load Sharing in Distributed Multimedia-on-Demand Systems

• Main Authors: TAY, Y. C., PANG, Hwee Hwa
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2000
• Subjects: Network servers; Analytical models; Bandwidth; Metropolitan area networks; Costs; Fluctuations; Joining processes; Multimedia systems; Load management; Algorithm design and analysis; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/113; https://ink.library.smu.edu.sg/context/sis_research/article/1112/viewcontent/Load_Sharing_in_Distributed_Multimedia_on_Demand_Systems__edited_.pdf
• Institution: Singapore Management University

Service providers have begun to offer multimedia-on-demand services to residential estates by installing isolated, small-scale multimedia servers at individual estates. Such an arrangement allows the service providers to operate without relying on a highspeed, large-capacity metropolitan area network, which is still not available in many countries. Unfortunately, installing isolated servers can incur very high server costs, as each server requires spare bandwidth to cope with fluctuations in user demand. The authors explore the feasibility of linking up several small multimedia servers to a (limited-capacity) network, and allowing servers with idle retrieval bandwidth to help out servers that are temporarily overloaded; the goal is to minimize the waiting time for service to begin. We identify four characteristics of load sharing in a distributed multimedia system that differentiate it from load balancing in a conventional distributed system. We then introduce a GWQ load sharing algorithm that fits and exploits these characteristics; it puts all servers' pending requests in a global queue, from which a server with idle capacity obtains additional jobs. The performance of the algorithm is captured by an analytical model, which we validate through simulations. Both the analytical and simulation models show that the algorithm vastly reduces wait times at the servers. The analytical model also provides guidelines for capacity planning. Finally, we propose an enhanced GWQ+L algorithm that allows a server to reclaim active local requests that are being serviced remotely. Simulation experiments indicate that the scheduling decisions of GWQ+L are optimal, i.e., it enables the distributed servers to approximate the performance of a large centralized server