| Summary: | 碩士 === 國立臺北科技大學 === 資訊工程系研究所 === 98 === Data Broadcasting is an effective approach to provide information to a large group of clients in ubiquitous environments. How to generate the data broadcast schedule to
make the average waiting time short for clients is an important issue. In particular, when the data access pattern is dynamic and data have time constraints, such as traffic and stock information, scheduling the broadcast for such data to fulfill the requests becomes challenging. Since the content of the broadcast is dynamic and the request deadlines should be met, such data broadcasting is referred to as on-demand data broadcasting with time constraints. Many related papers discussed this type of data broadcasting with a single broadcast channel. In this thesis, we investigate how to schedule the on-demand broadcast for the data with time constraints using multiple broadcast channels and provide two heuristics to schedule the data broadcast. The objective of the proposed heuristics is to minimize the miss rate (i.e., ratio of the requests missing deadlines to all the requests) and latency (i.e., time between issuing and termination of the request).
Besides, we prove that the problem is NP-Hard when the access pattern is offline. We also present a competitive analysis on the proposed heuristics. More discussion about
the proposed heuristics is given through extensive simulation experiments. The experimental results validate that the proposed heuristics achieve the objectives.
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