A caching mechanism to accelerate pattern matching queries involving big graphs
Manda, Satya Vikas
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Using graph indexing and decomposing techniques to speed up graph pattern matching are known approaches. However, the size of graphs representing social networks and biological networks have become so massive that it is challenging both in terms of response time and computational intensity to carry out the task of pattern-matching. With the advent graph simulation models the time complexity of pattern-matching has been reduced to a polynomial factor. Indeed, an efficient caching strategy designed specifically for graph pattern-matching using simulation techniques can greatly impact the query answering performance for massive graphs both in a centralized or a distributed setting. This research presents the challenges involved in designing such a system and introduces a novel caching mechanism that is developed based on the observations made through a comprehensive experimental study involving comparison among various concepts involved. The efficiency of our approach is also verified through a precise set of experiments.