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Due to increased interests in interactive personalized multimedia services, the design of continuous media (CM) severs in support of this functionality has received attention from industry and academia. These systems automatically create a sequence of CM segments optimized to the interests of each user based on their predefined preferences and impromptu queries. Applications such as distance learning, news-on-demand, interactive training, and home shopping would be significantly improved with this functionality. Two critical issues are 1) automatic creation of an optimized script for each user, and 2) data management and retrieval to maximize the performance of servers in a multi-user environment. Due to the maximized flexibility of presentation and potential conflicts among requirements from concurrent users while sharing huge amount of CM data without redundancy, the design of a CM sever that supports these applications, especially data placement and retrieval scheduling, is challenging. This paper investigates and proposes data placement and retrieval scheduling techniques on multi-disk CM servers to support such applications. These include how to share the same content among multiple users, how to compose a personalized content on demand for each user and support continuous display of the edited content without any jitters or interruptions, termed hiccups. The proposed techniques solve the problems by providing a fast retrieval of CM data using random data placement across disks with deadline-driven scheduling and prefetching them with a minimal latency to statistically guarantee a continuous display. Simulation results demonstrate the feasibility of on-demand composition and continuous display of personalized content with a hiccup probability less than a millionth. They also show less than a second startup latency, which is acceptable for most interactive applications.
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