Computer Science ›› 2016, Vol. 43 ›› Issue (5): 179-187.doi: 10.11896/j.issn.1002-137X.2016.05.033

Previous Articles     Next Articles

Research of Interval-based Out-of-order Event Processing in Internet of Things

ZHOU Chun-jie, DAI Peng-fei, LI Hong-bo and ZHANG Zhen-xing   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Many events in real world applications are long-lasting events which have certain durations.The temporal relationships among those durable events are often changeable and complex.Moreover,when there are out-of-order events,the query processing becomes more challenging.In applications of internet of things,ordered arriving of order events is strictly required.However,network latencies and machine failures often cause events to be out-of-order.In this work,we analyzed the preliminaries of event temporal semantics.A tree-plan model of out-of-order durable events was proposed.A hybrid solution was correspondingly introduced.Extensive experimental studies demonstrate the efficiency of our approach.

Key words: Interval-based,Internet of things,Out-of-order events,Temporal semantic

[1] Mei Y,Madden S.ZStream:a cost-based query processor foradaptively detecting composite events[C]∥Proceedings of the 35th SIGMOD International Conference on Management of Data.SIGMOD,2009:193-206
[2] Antunes C,Oliveira A L.Generalization of pattern growth me-thods for sequential pattern mining with gap constraints[M].Machine Learning and Data Mining in Pattern Recognition.2003:239-251
[3] Pei J,Han J,Mortazavi B,et al.Prefixspan:mining sequential patterns efficiently by prefix-projected pattern growth[C]∥Proceedings of the 17th International Conference on Data Engineering(ICDE).2001:215-226
[4] Wu E,Diao Y,Rizvi S.High performance complex event processing over streams[C]∥Proceedings of the 32th SIGMOD International Conference on Management of Data.SIGMOD,2006:407-418
[5] Alex D,Robert R,Subrahmanian V S.Probabilistic temporal databases[J].ACM Transaction on Database Systems,2001,26(1):41-95
[6] Barga R S,Goldstein J,Ali M,et al.Consistent streaming th-rough time:a vision for event streamprocessing[C]∥The 3rd Biennial Conference on Innovative Data Systems Research.IDAR,2007
[7] Wu S,Chen Y,Mining nonambiguous temporal patterns for interval-based events[J].IEEE Transactions on Knowledge and Data Engineering,2007,19(6):742-758
[8] Patel D,Hsu W,Lee M L.Mining relationships among interval-based events for classification[C]∥Proceedings of the 34th SIGMOD International Conference on Management of Data.SIGMOD,2008:393-404
[9] Hammad M A,et al.Scheduling for shared window joins over data streams[C]∥The 29th International Conference on Very Large Data Bases.2003,29:297-308
[10] Liu M,Li M,Golovnya D,et al.Sequence pattern query proces-sing over out-of-order event streams[C]∥Proceedings of the 25th International Conference on Data Engineering(ICDE).2009:274-295
[11] Eyerman S,Eeckhout L,Karkhanis T,et al.A mechanistic performance model for superscalar out-of-order processors[J].ACM Transactions on Computer Systems(TOCS),2009,27(2):824-833
[12] Wang F,Liu S,Liu P.Complex RFID event processing[J].The International Journal on Very Large Data Bases(VLDBJ),2009,18(4):913-931
[13] Papapetrou P,Kollios G,Sclaroff S,et al.Mining frequent arrangements of temporal intervals[J].Knowledge & Information Systems,2009,1(2):133-171
[14] Ding L,Mehta N,Rundensteiner E A,et al.Joining punctuated streams[M]∥Advances in Database Technology(EDBT).2004:587-604
[15] Kam P S,Fu A W.Discovering temporal patterns for interval-based events[C]∥Proceedings of the 2nd International Confe-rence on Data Warehousing and Knowledge Discovery.2000:317-326
[16] Barga R S,Goldstein J,Ali M,et al.Consistent streaming th-rough time:a vision for event stream processing[C]∥The 3rd Biennial Conference on Innovative Data Systems Research.2006:363-374
[17] Zhou C J,Meng X F.A framework of complex event detection and operation in pervasive computing[C]∥The Third SIGMOD PhD Workshop on Innovative Database Research.2009

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!