The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems
TAG: a Tiny AGgregation service for ad-hoc sensor networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
Transforming BPEL into Annotated Deterministic Finite State Automata for Service Discovery
ICWS '04 Proceedings of the IEEE International Conference on Web Services
Network-Aware Operator Placement for Stream-Processing Systems
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
High-performance complex event processing over streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Network-aware query processing for stream-based applications
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
In-network event processing in a peer to peer broker network for the internet of things
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems - Volume Part II
Distributed Event-Based Systems
Distributed Event-Based Systems
Composite event detection as a generic middleware extension
IEEE Network: The Magazine of Global Internetworking
Guest editorial: Advances in RFID technology
Information Systems Frontiers
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Integrating RFID data from various sources in a value chain is an important requirement for leveraging the full potential of the technology. To facilitate this crucial integration, the global standardization organization GS1 is currently developing a range of service specifications. Yet, the services specified so far do not enable event-based interaction schemes and do not leverage the detection of distributed complex events. In this paper we propose to fill this gap by means of a peer-to-peer based broker network that can realize event-based interaction on top of existing specifications. For this infrastructure we present a new method to improve in-network processing. As shown by our experiments, our method significantly reduces overall system load by exploiting a priori knowledge about the observed processes.