Browsing by Author "Dougherty, D. J."

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    Conference paperPublicationMetadata only
    Optimizing complex sequence pattern extraction using caching
    (IEEE, 2011) Ray, M.; Lui, M.; Rundensteiner, E.; Dougherty, D. J.; Gupta, C.; Wang, S.; Mehta, A.; Arı, İsmail; Computer Science; ARI, Ismail
    Complex Event Processing (CEP) has become increasingly important for tracking and monitoring complex event anomalies and trends in event streams emitted from business processes such as supply chain management to online stores in e-commerce. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. The state-of-the-art CEP systems mostly focus on the execution of flat sequence queries, we instead support the execution of nested CEP queries specified by our NEsted Event Language NEEL. However, the iterative execution of nested CEP expressions often results in the repeated recomputation of the same or similar results for nested subexpressions as the window slides over the event stream. In this work we thus propose to optimize NEEL execution performance by caching intermediate results. In particular we design two methods of applying selective caching of intermediate results namely Object Caching and the Interval-Driven Semantic Caching. Techniques for incrementally loading, purging and exploiting the cache content are described. Our experimental study using real-world stock trades evaluates the performance of our proposed caching strategies for different query types.
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    Conference paperPublicationOpen Access
    Processing nested complex sequence pattern queries over event streams
    (ACM, 2010) Liu, M.; Ray, M.; Rundensteiner, E. A.; Dougherty, D. J.; Gupta, C.; Wang, S.; Arı, İsmail; Mehta, A.; Computer Science; ARI, Ismail
    Complex event processing (CEP) has become increasingly important for tracking and monitoring applications ranging from healthcare, supply chain management to surveillance. These monitoring applications submit complex event queries to track sequences of events that match a given pattern. As these systems mature the needfor increasingly complex nested sequence queries arises, while thestate-of-the-art CEP systems mostly focus on the execution of flat sequence queries only. In this paper, we now introduce an iterative execution strategy for nested CEP queries composed of sequence, negation, AND and OR operators. Lastly the promise of applying selective caching of intermediate results to optimize the execution. Our experimental study using real-world stock trades evaluates the performance of our proposed iterative execution strategy for differentquery types.
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    Realtime healthcare services via nested complex event processing technology
    (The ACM Digital Library, 2012) Liu, M.; Ray, M.; Zhang, D.; Rundensteiner, E.; Dougherty, D. J.; Gupta, C.; Wang, S.; Arı, İsmail; Computer Science; ARI, Ismail
    Complex Event Processing (CEP) over event streams has become increasingly important for real-time applications ranging from healthcare to supply chain management. In such applications, arbitrarily complex sequence patterns as well as non existence of such complex situations must be detected in real time. To assure real-time responsiveness for detection of such complex pattern over high volume high-speed streams, efficient processing techniques must be designed. Unfortunately the efficient processing of complex sequence queries with negations remains a largely open problem to date. To tackle this shortcoming, we designed optimized strategies for handling nested CEP query. In this demonstration, we propose to showcase these techniques for processing and optimizing nested pattern queries on streams. In particular our demonstration showcases a platform for specifying complex nested queries, and selecting one of the alternative optimized techniques including sub-expression sharing and intermediate result caching to process them. We demonstrate the efficiency of our optimized strategies by graphically comparing the execution time of the optimized solution against that of the default processing strategy of nested CEP queries. We also demonstrate the usage of the proposed technology in several healthcare services.