An efficient Intelligent Cache Replacement Policy Suitable for PACS

An efficient intelligent cache replacement policy suitable for picture archiving and communication systems (PACS) was proposed in this work. By combining the Support vector machine (SVM) with the classic least recently used (LRU) cache replacement policy, we have created a new intelligent cache replacement policy called SVM-LRU. The SVM-LRU policy is unlike conventional cache replacement policies, which are solely dependent on the intrinsic properties of the cached items. Our PACS-oriented SVM-LRU algorithm identifies the variables that affect file access probabilities by mining medical data. The SVM algorithm is then used to model the future access probabilities of the cached items, thus improving cache performance. Finally, a simulation experiment was performed using the trace-driven simulation method. It was shown that the SVM-LRU cache algorithm significantly improves PACS cache performance when compared to conventional cache replacement policies like LRU, LFU, SIZE and GDS.

Intelligent Cache Management for Mobile Data Warehouse Systems

This research proposes an intelligent cache mechanism for a data warehouse system in a mobile environment. Because mobile devices can often be disconnected from the host server and due to the low bandwidth of wireless networks, it is more efficient to store query results from a mobile device in the cache. For more personal use of mobile devices, we use a data mining technique to determine the pattern from a record of previous queries. Then the data, which will be retrieved by the user, are prefetched and stored in the cache, thus, improving the query efficiency. We demonstrate the feasibility of the proposed approach with experiments using simulation. Comparison of our approach with a standard approach indicates that there is a significant advantage to using mobile data warehouse systems.