Abstract
Although storage technologies are in great progress, hierarchical storage is still an efficient way to manage massive data, especially massive Continuous Media (CM) data. In some large web based CM applications such as DL (Digital Library) and VOD (Video-On-Demand), cache replacement algorithms are used to keep the hot data on the disk, and migrate out those rarely accessed. The existing algorithms always treat all files equally, and use cache miss rate to evaluate the performance. However, in actual CM applications, most video objects are stored as several separated files that will be played one by one, so the strong relationships among the access time of these files make pre-fetch practicable and efficient. If all the files are taken as the same, the performance of systems will degrade. Meanwhile, the cache miss rate cannot evaluate the performance comprehensively. In this paper, a new metric, User Waiting Rate, is defined to evaluate the performance, and a novel cache replacement algorithm, Least Waiting Probability (LWP) algorithm, is proposed. Experiment results show that it can improve the performance a lot, and is highly adaptive.
Supported by the National Natural Science Foundation of China under Grant No. 60221120146; the National Grand Fundamental Research 973 Program of China under Grant No.G1999032704.
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Xu, Y., Xing, C., Zhou, L. (2004). A Cache Replacement Algorithm in Hierarchical Storage of Continuous Media Object. In: Li, Q., Wang, G., Feng, L. (eds) Advances in Web-Age Information Management. WAIM 2004. Lecture Notes in Computer Science, vol 3129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27772-9_17
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DOI: https://doi.org/10.1007/978-3-540-27772-9_17
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