Reliable complex event detection for pervasive computing

Complex event processing for pervasive computing must deal with various sources of error. In this paper, we focus on improving complex event detector handling of several types of communication error, in addition to timing errors caused by the lack of a global clock in distributed systems. We propose extensions to a complex event language that allow programmers specify a variety of detection policies. Although not a panacea, these policies help detectors tolerate a variety of errors such that the output they produce is sensible with respect to the semantics required by individual applications. Of particular interest is a detection policy that ensures no false positives are received. We discuss in detail the implementation of such a policy and the factors that influence its effectiveness. Finally, we evaluate an implementation of our policy, and show how performance is unaffected during normal operation, but that overhead increases with the number of errors.

[1]  Morris Sloman,et al.  GEM: a generalized event monitoring language for distributed systems , 1997, Distributed Syst. Eng..

[2]  Anne-Marie Kermarrec,et al.  The many faces of publish/subscribe , 2003, CSUR.

[3]  Sharma Chakravarthy,et al.  Composite Events for Active Databases: Semantics, Contexts and Detection , 1994, VLDB.

[4]  Opher Etzion,et al.  Amit - the situation manager , 2003, The VLDB Journal.

[5]  Andrey Brito,et al.  Speculative out-of-order event processing with software transaction memory , 2008, DEBS.

[6]  Peter Pietzuch Hermes: A scalable event-based middleware , 2004 .

[7]  Alejandro P. Buchmann,et al.  Event composition in time-dependent distributed systems , 1999, Proceedings Fourth IFCIS International Conference on Cooperative Information Systems. CoopIS 99 (Cat. No.PR00384).

[8]  Michael Stonebraker,et al.  Monitoring Streams - A New Class of Data Management Applications , 2002, VLDB.

[9]  Hans-Arno Jacobsen,et al.  Composite Subscriptions in Content-Based Publish/Subscribe Systems , 2005, Middleware.

[10]  Sharma Chakravarthy,et al.  Formal semantics of composite events for distributed environments , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[11]  Hector Garcia-Molina,et al.  Replicated condition monitoring , 2001, PODC '01.

[12]  Jonathan Goldstein,et al.  Consistent Streaming Through Time: A Vision for Event Stream Processing , 2006, CIDR.

[13]  Qiang Chen,et al.  Aurora : a new model and architecture for data stream management ) , 2006 .

[14]  Peter R. Pietzuch,et al.  Composite event detection as a generic middleware extension , 2004, IEEE Network.

[15]  Stanley B. Zdonik,et al.  Revision Processing in a Stream Processing Engine: A High-Level Design , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[16]  Jennifer Widom,et al.  Query Processing, Resource Management, and Approximation ina Data Stream Management System , 2002 .

[17]  Scarlet Schwiderski-Grosche Monitoring the behaviour of distributed systems , 1996 .

[18]  Martin Bauer Event management for mobile users , 2004 .

[19]  Ken Moody,et al.  An open architecture for secure interworking services , 1996, EW 7.