SIGMOD '95 Proceedings of the 1995 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
Proactive Power-Aware Cache Management for Mobile Computing Systems
IEEE Transactions on Computers
Semantic Caching and Query Processing
IEEE Transactions on Knowledge and Data Engineering
Location-based spatial queries
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Nearest Neighbor Search: A Database Perspective
Nearest Neighbor Search: A Database Perspective
An Energy-Efficient and Access Latency Optimized Indexing Scheme for Wireless Data Broadcast
IEEE Transactions on Knowledge and Data Engineering
Adaptive data dissemination schemes for location-aware mobile services
Journal of Systems and Software - Special issue: Quality software
Cache Strategies for Semantic Prefetching Data
WAIMW '06 Proceedings of the Seventh International Conference on Web-Age Information Management Workshops
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
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In mobile computing environments, a user's mobility and query patterns are multiform. To support an adequate service to the user within quick period, it is important to consider the user's various interests. As the development of the mobile device, the work of client-side has been getting more and more without continuous connection between client and server. However, the minimized communication costs are needed to keep a consistency with server. This paper uses a sematic prefetching scheme with the aim of decreasing the communication cost, and depicts various cache replacement policies. Moreover, considering a client's description parameters (access time, frequency, locality), a range query and a nearest neighbor query are dynamically performed according to user patterns. Our experiment results show that the proposed preference priority replacement policy outperforms other policies, and has the better performance when adjusting the ratio of query type (range and nearest neighbor queries) with respect to mobility (high, low) and query patterns (various, similar).