Accelerating Dynamic Web Content Generation
IEEE Internet Computing
STEP: Self-Tuning Energy-safe Predictors
Proceedings of the 6th international conference on Mobile data management
Database research at Bilkent University
ACM SIGMOD Record
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
New prediction model for pre-fetching in mobile database
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
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One of the features that a mobile computer should provide is disconnected operation which is performed by hoarding. The process of hoarding can be described as loading the data items needed in the future to the client cache prior to disconnection. Automated hoarding is the process of predicting the hoard set without any user intervention. In this paper, we describe an application independent and generic technique for determining what should be hoarded prior to disconnection.Our method utilizes association rules that are extracted by data mining techniques for determining the set of items that should be hoarded to a mobile computer prior to disconnection. The proposed method was implemented and tested on synthetic data to estimate its effectiveness. Performance experiments determined that the proposed rule-based methods are effective in improving the system performance in terms of the cache hit ratio of mobile clients especially for small cache sizes.