NDLI: Using Hypergraph-based Clustering Scheme for Traversal Prediction in Virtual Environments

Content Provider	IEEE Xplore Digital Library
Author	Shao-Shin Hung Shing-Min Liu, D.
Copyright Year	2007
Description	Author affiliation: Dept. of Comput. Sci. & Inf. Eng., National Chung Cheng Univ., Chiayi (Shao-Shin Hung; Shing-Min Liu, D.)
Abstract	In many virtual environments (VE) applications, the size of the database is not only extremely large, it is also growing rapidly. Even for relatively simple searches, the time required to move the data off storage media is expensive. However, object correlations are common semantic patterns in VE. They can be exploited for improve the effectiveness of storage caching, prefetching, data layout, and disk scheduling. However, little approaches for discovering object correlations in VE to improve the performance of storage systems. In this paper, we develop a class of view-based projection-generation method for mining various frequent sequential traversal patterns in the VE. The frequent sequential traversal patterns are used to predict the user navigation behavior. Furthermore, the hypergraph-based clustering scheme can help reduce disk access time with proper placement patterns into disk blocks. Finally, we have done extensive experiments to demonstrate how these proposed techniques not only significantly cut down disk access time, but also enhance the accuracy of data prefetching
Starting Page	429
Ending Page	436
File Size	9957550
Page Count	8
File Format	PDF
ISBN	1424407052
DOI	10.1109/CIDM.2007.368906
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Virtual environment Databases Navigation Prefetching Memory Size measurement Data mining Delay Computational intelligence
Content Type	Text
Resource Type	Article

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