Events Calendar

PhD Defense - Qunzhi Zhou

Title: A Complex Event Processing Framework for Holistic Fast Data Management

Ph.D Candidate: Qunzhi Zhou

Defense Committee:
Viktor Prasanna (Co-Chair)
Yogesh Simmhan (Co-Chair)
Ellis Horowitz
Petros Ioannou

Time: 2:00 PM - 4:00 PM @ Wednesday, May 14, 2014

Location: Hughes Aircraft Electrical Engineering Building (EEB) 248

Abstract:
Emerging applications in domains like Smart Grid, e-commerce and financial services have been motivating Fast Data which emphasizes the Velocity aspect of Big Data. Utility companies, social media and financial institutions often face scenarios where they need to process data arriving continuously at high rate for businesses innovation and analytics. Existing Big Data management systems however have mostly focused on the Volume aspect of Big Data. Systems including Hadoop and NoSQL databases provide programming and query primitives that allow scalable storage and querying of very large data sets. These systems are best suited for applications that perform write-once-read-many operations on slow-changing data volumes for their focuses on data availability and read performance.

Complex Event Processing (CEP), on the other hand, is a promising paradigm to manage Fast Data. CEP is recognized for online analytics of data that arrive continuously from ubiquitous, always-on sensors and digital event streams. It allows event patterns composed with correlation constraints, also called complex events, to be detected from examining event streams in realtime for situation awareness. Specifically, CEP adopts high throughput temporal pattern matching algorithms to handle data Velocity. As a result, CEP has grown popular for operational intelligence where online pattern detection drives realtime response.

Fast Data management motivates certain distinctive capabilities from CEP systems to deal with concurrent data Variety, Volume and Velocity. In this dissertation, we present a Complex Event Processing framework for holistic Fast Data management that considers all the 3 V’s. In particular, we extend the state-of-the-art CEP systems and make the following contributions: 1) Semantic Complex Event Processing for on-the-fly query processing over diverse data streams, shielding data and domain Varieties; 2) Stateful Complex Event Processing that provides a hierarchical query paradigm for dynamic stream Volume management and on-demand query evaluation; 3) Resilient Complex Event Processing that supports integrated querying across low-Velocity data archives and realtime data streams. We perform quantitative evaluations using real-world applications from Smart Grid domain to verify the efficacy of the proposed framework and demonstrate the performance benefits of the optimization techniques.

Bio:
Qunzhi Zhou is currently a PhD candidate in the Computer Science Department at the University of Southern California. His research interests are in information integration, stream processing and distributed computing systems. He has a M.S. in Computer Science from University of Southern California and received his B.S. in Automation from Tsinghua University, China.

Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

Audiences: Everyone Is Invited

Contact: Lizsl De Leon