TY - GEN
T1 - Complex event processing over uncertain data streams
AU - Kawashima, Hideyuki
AU - Kitagawa, Hiroyuki
AU - Li, Xin
PY - 2010/12/1
Y1 - 2010/12/1
N2 - Pattern matching over event streams is well developed. However, with the increasing demand of measurement accuracy, confidence of more complex events sourced from original, continuously arriving events generated from sensor kind electronic devices is becoming more and more been concerned. Actually, some applications such as RFID-based supply chain management and monitoring in health care require data stream with high reliability, but current hardware and wireless communication techniques cannot support 100% confident data, one stream processing engine which can report confidence for processed complex events over uncertain data is needed. In this paper, we propose an optimized method to not only calculate the probability of outputs of compound events but also obtain the value of confidence of the complex pattern given by user against uncertain raw input data stream generated by distrustful network devices. Our proposal is based on an existing stream processing engine SASE+, and we extend its evaluation model NFAb automaton to a new type of automaton in order to manage the runtime against probabilistic stream. In the design of automaton, we consider optimizations to reduce the computation cost and response time to a realistic degree with long sliding time window.
AB - Pattern matching over event streams is well developed. However, with the increasing demand of measurement accuracy, confidence of more complex events sourced from original, continuously arriving events generated from sensor kind electronic devices is becoming more and more been concerned. Actually, some applications such as RFID-based supply chain management and monitoring in health care require data stream with high reliability, but current hardware and wireless communication techniques cannot support 100% confident data, one stream processing engine which can report confidence for processed complex events over uncertain data is needed. In this paper, we propose an optimized method to not only calculate the probability of outputs of compound events but also obtain the value of confidence of the complex pattern given by user against uncertain raw input data stream generated by distrustful network devices. Our proposal is based on an existing stream processing engine SASE+, and we extend its evaluation model NFAb automaton to a new type of automaton in order to manage the runtime against probabilistic stream. In the design of automaton, we consider optimizations to reduce the computation cost and response time to a realistic degree with long sliding time window.
KW - Complex Event Processing
KW - Data Stream
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=84859779484&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84859779484&partnerID=8YFLogxK
U2 - 10.1109/3PGCIC.2010.89
DO - 10.1109/3PGCIC.2010.89
M3 - Conference contribution
AN - SCOPUS:84859779484
SN - 9780769542379
T3 - Proceedings - International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2010
SP - 521
EP - 526
BT - Proceedings - International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2010
T2 - 5th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2010
Y2 - 4 November 2010 through 6 November 2010
ER -