Complex Event Analytics

The recent advances in hardware and software have enabled the capture of different measurements of data in a wide range of fields. Applications that generate rapid, continuous and large volumes of event streams include readings from sensors used in applications, such as physics, biology and chemistry experiments, weather sensors, health sensors, network sensors, online auctions, credit card operations, financial tickers, web server log records, etc. Given these developments, the world is poised for a sea-change in terms of variety, scale and importance of applications that can be envisioned based on the real-time analysis and exploitation of such event stream for decision making - from dynamic traffic management, environmental monitoring to health care alike. Clearly, the ability to infer relevant patterns from these event streams in real-time to make near instantaneous yet informed decisions, henceforth called complex event analytics, is absolutely crucial for these mission critical applications.

Acknowledgments: This work is supported by NSF Project IIS-1018443, HP Lab Innovation Research Grant and UMMS-WPI  CCTS Collaborative Grant.

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