TY - GEN
T1 - Event stream processing with out-of-order data arrival
AU - Li, Ming
AU - Liu, Mo
AU - Ding, Luping
AU - Rundensteiner, Elke A.
AU - Mani, Murali
PY - 2007
Y1 - 2007
N2 - Complex event processing has become increasingly important in modern applications, ranging from supply chain management for RFID tracking to real-time intrusion detection. The goal is to extract patterns from such event streams in order to make informed decisions in real-time. However, networking latencies and even machine failure may cause events to arrive out-of-order at the event stream processing engine. In this work, we address the problem of processing event pattern queries specified over event streams that may contain out-of-order data. First, we analyze the problems state-of-the-art event stream processing technology would experience when faced with out-of-order data arrival. We then propose a new solution of physical implementation strategies for the core stream algebra operators such as sequence scan and pattern construction, including stack-based data structures and associated purge algorithms. Optimizations for sequence scan and construction as well as state purging to minimize CPU cost and memory consumption are also introduced. Lastly, we conduct an experimental study demonstrating the effectiveness of our approach.
AB - Complex event processing has become increasingly important in modern applications, ranging from supply chain management for RFID tracking to real-time intrusion detection. The goal is to extract patterns from such event streams in order to make informed decisions in real-time. However, networking latencies and even machine failure may cause events to arrive out-of-order at the event stream processing engine. In this work, we address the problem of processing event pattern queries specified over event streams that may contain out-of-order data. First, we analyze the problems state-of-the-art event stream processing technology would experience when faced with out-of-order data arrival. We then propose a new solution of physical implementation strategies for the core stream algebra operators such as sequence scan and pattern construction, including stack-based data structures and associated purge algorithms. Optimizations for sequence scan and construction as well as state purging to minimize CPU cost and memory consumption are also introduced. Lastly, we conduct an experimental study demonstrating the effectiveness of our approach.
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U2 - 10.1109/ICDCSW.2007.35
DO - 10.1109/ICDCSW.2007.35
M3 - Conference contribution
AN - SCOPUS:35948979665
SN - 0769528384
SN - 9780769528380
T3 - Proceedings - International Conference on Distributed Computing Systems
SP - 67
EP - 74
BT - 27th International Conference on Distributed Computing Systems Workshops, ICDCSW'07
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th International Conference on Distributed Computing Systems Workshops, ICDCSW'07
Y2 - 22 June 2007 through 29 June 2007
ER -