Efficient Matching in Heterogeneous Rule Engines

Modern institutions seeking more complex software solutions to represent knowledge in the Cloud are using rule-based systems that serve several applications or clients. Rule-based systems hosted in the Cloud are thus required to support its heterogeneous nature. However, current systems only focus on techniques that isolate instances of rule engines. This paper builds upon earlier work on scoped rule engines that provide mechanisms for supporting shared heterogeneous contexts. We present the scope-based hashing algorithm (SBH) that enables efficient matching in scoped rule engines based on the Rete algorithm. SBH introduces scoped hash tables in alpha memories that help in avoiding unnecessary join tests that hamper performance. Our experimental results show that SBH offers significant improvements in efficiency during the matching process of a heterogeneous rule engine. Consequently, SBH significantly decreases the response time of rule engines in heterogeneous environments having entities sharing the same knowledge base.