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The performance bottleneck of transparent computing (TC) is on the server side. Caching is one of the key factors of the server-side performance. The count of disk input/output (I/O) can be reduced if multiple data blocks that are correlated with the data block currently accessed are prefetched in advance. As a result, the service performance and user experience quality in TC can be improved. In this study, we propose a caching strategy for the TC server side based on data block relevance, which is called the correlation pattern-based caching strategy (CPCS). In this method, we adjust a model that is based on a frequent pattern tree (FP-tree) for mining frequent patterns from data streams (FP-stream) to the characteristics of data access in TC, and we devise a cache structure in accordance with the storage model of TC. Finally, the access process in TC with real access traces in different caching strategies. Simulation results show that the cache hit rate under the CPCS is higher than that using other algorithms under conditions in which the parameters are coordinated properly.

A Caching Strategy for Transparent Computing Server Side Based on Data Block Relevance