The Research on CEP Based on Query Rewriting for CPS

Abstract

Now we are entering the era of Big Data, and the important data source of which is Cyber Physical System (CPS) data, those data can hardly be processed by present data processing technology. Complex Event Processing (CEP) is the key part of middleware of CPS, which can process the big data, and context-awareness is an important feature of CEP engine. There are some challenges in context-aware complex event processing for CPS, such as heterogeneous, massive data, distributed event processing, uncertainly; therefore, we propose a distributed context-aware event processing method, based on context representation proposed fuzzy ontology and a distributed multi-level context reasoning method to support uncertainty and linguistic variables in event queries. Based on fuzzy ontology query and similarity based distributed reasoning, complex event query plans are generated and context-aware queries are rewritten into context independent sub-queries. Data window is partitioned according to different event patterns and context. The sub-queries are optimized and executed parallel based on data partition. The experiments show that this method can support fuzzy context in CEP and have acceptable performance and scalability.