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<p><b>Abstract</b>—Distributed information processing, in many world wide web applications, requires access, transfer, and synchronization of large multimedia data objects (MDOs) (such as, audio, video, and images) across the communication network. Moreover, the end users have started expecting very fast response times and high quality of service. Since the transfer of large MDOs across the communication network contributes to the response time observed by the end users, the problem of allocating these MDOs so as to minimize the response time becomes very challenging. This problem becomes more complex in the context of hypermedia documents (web pages), wherein the MDOs need to be synchronized during presentation to the end users. Note that the basic problem of data allocation in distributed database environments is NP-complete. Therefore, there is a need to pursue and evaluate solutions based on heuristics which generate near-optimal MDO allocation. In this paper, we address this problem by: 1) conceptualizing this problem by using a navigational model to represent hypermedia documents and their access behavior from end users, and by capturing the synchronization requirements on MDOs, 2) formulating the problem by developing a base case cost model for response time, and generalizing it to incorporate user interaction and buffer memory constraints, 3) designing two algorithms to find near-optimal solutions for allocating MDOs of the hypermedia documents while adhering to the synchronization requirements, and 4) evaluating the trade-off between the time complexity to get the solution and the quality of solution by comparing the solutions generated by the algorithms with the optimal solutions generated through an exhaustive search.</p>
Data allocation, response time, multimedia data objects, hypermedia documents, distributed hypermedia document systems, navigational model.

S. So, K. Karlapalem and I. Ahmad, "Response Time Driven Multimedia Data Objects Allocation for Browsing Documents in Distributed Environments," in IEEE Transactions on Knowledge & Data Engineering, vol. 11, no. , pp. 386-405, 1999.
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