An incremental access method for ViewCache: concept, algorithms, and cost analysis
ACM Transactions on Database Systems (TODS)
Sleepers and workaholics: caching strategies in mobile environments
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Using semantic caching to manage location dependent data in mobile computing
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Location dependent query processing
Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
Semantic query caching in a mobile environment
ACM SIGMOBILE Mobile Computing and Communications Review
Semantic Caching and Query Processing
IEEE Transactions on Knowledge and Data Engineering
Performance Analysis of Location-Dependent Cache Invalidation Schemes for Mobile Environments
IEEE Transactions on Knowledge and Data Engineering
Semantic Data Caching and Replacement
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Strategies for Semantic Caching
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Efficient indexing of the historical, present, and future positions of moving objects
Proceedings of the 6th international conference on Mobile data management
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Dissemination techniques of data have been rapidly developed for wireless communication environment. Since the advent of ubiquitous computing, semantic-based researches have been sped-up between service provider and user. We have tried to maintain user information with a semantic cache scheme. In this paper, we propose a semantic prefetching (SP) strategy for efficient data management, considering semantic information of user. We concentrate on data prefetching methods to send mass data to high bandwidth channels. In the SP, the prepared semantic descriptions are prefetched from server to client according as the client locates in anywhere. The semantic descriptions are dynamically composed of user patterns, such as the request patterns of user, the size of querying area, the direction of user and the average speed of user. We also propose a new cache management scheme, called to semantic least recently used (S-LRU). The evaluation result shows that the system performance is significantly improved.