TY - GEN
T1 - Comet
T2 - 2012 IEEE 13th International Conference on Mobile Data Management, MDM 2012
AU - Chen, Jianxia
AU - Ramaswamy, Lakshmish
AU - Lowenthal, David K.
AU - Kalyanaraman, Shivkumar
PY - 2012
Y1 - 2012
N2 - Increased commodity use of mobile devices has the potential to enable mission-critical monitoring applications. However, these mobile-enabled monitoring applications have to often work in environments where a delay-tolerant network (DTN) is the only feasible communication paradigm. Detection of complex (composite) events is fundamental to monitoring applications. However, the existing plan-based CED techniques are mostly centralized, and hence are inherently unscalable for DTNs. In this paper, we create Comet - a decentralized plan-based, efficient and scalable CED for DTNs. Comet shares the task of detecting complex events (CEs) among multiple nodes, with each node detecting a part of the CE by aggregating two or more primitive events or sub-CEs. Comet uses a unique h-function to construct cost and delay efficient CED trees. As finding an optimal CED plan requires exponential-time, Comet finds near-optimal detection plans for individual CEs through a novel multi-level push-pull conversion algorithm. Performance results show that Comet reduces cost by up to 89% compared to pushing all primitive events and over 60% compared to a two-level exhaustive search algorithm.
AB - Increased commodity use of mobile devices has the potential to enable mission-critical monitoring applications. However, these mobile-enabled monitoring applications have to often work in environments where a delay-tolerant network (DTN) is the only feasible communication paradigm. Detection of complex (composite) events is fundamental to monitoring applications. However, the existing plan-based CED techniques are mostly centralized, and hence are inherently unscalable for DTNs. In this paper, we create Comet - a decentralized plan-based, efficient and scalable CED for DTNs. Comet shares the task of detecting complex events (CEs) among multiple nodes, with each node detecting a part of the CE by aggregating two or more primitive events or sub-CEs. Comet uses a unique h-function to construct cost and delay efficient CED trees. As finding an optimal CED plan requires exponential-time, Comet finds near-optimal detection plans for individual CEs through a novel multi-level push-pull conversion algorithm. Performance results show that Comet reduces cost by up to 89% compared to pushing all primitive events and over 60% compared to a two-level exhaustive search algorithm.
KW - CED Trees
KW - Event composition
KW - Multi-level pushpull conversion
UR - http://www.scopus.com/inward/record.url?scp=84870730072&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84870730072&partnerID=8YFLogxK
U2 - 10.1109/MDM.2012.18
DO - 10.1109/MDM.2012.18
M3 - Conference contribution
AN - SCOPUS:84870730072
SN - 9780769547138
T3 - Proceedings - 2012 IEEE 13th International Conference on Mobile Data Management, MDM 2012
SP - 131
EP - 136
BT - Proceedings - 2012 IEEE 13th International Conference on Mobile Data Management, MDM 2012
Y2 - 23 July 2012 through 26 July 2012
ER -