Complex RFID event processing

Wang, Fusheng; Liu, Shaorong; Liu, Peiya

doi:10.1007/s00778-009-0139-0

Cited by 86 publications

(54 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The basic events happen in the application of RFID means the action that the RFID readers fetch the object"s tag [6] and every basic event happens at a time point.…”

Section: Related Research Foundation Definitionmentioning

confidence: 99%

A Research of Sensors Complementary for the RFID Wireless Network based on the Variable Coverage Radius

Wang¹,

Zhao²,

Zhou³

2016

IJFGCN

View full text Add to dashboard Cite

In order to solve the problems of sensors complementary, algorithm sensors complementary for the RFID wireless network is proposed in this paper. Based upon the fundamental definitions about the probabilistic events and the data generated by the particle filtering algorithm, the paper considers the factors of the number of locations covered and the probability the object appears. In view of the definition of the covering variability and the cover ratio, 5kinds of RFID sensors covering radius are considered. Finally, the experiment is carried out in order to improve the algorithm's availability and effectiveness.

show abstract

“…The basic events happen in the application of RFID means the action that the RFID readers fetch the object"s tag [6] and every basic event happens at a time point.…”

Section: Related Research Foundation Definitionmentioning

confidence: 99%

A Research of Sensors Complementary for the RFID Wireless Network based on the Variable Coverage Radius

Wang¹,

Zhao²,

Zhou³

2016

IJFGCN

View full text Add to dashboard Cite

show abstract

“…The two methods of generalizations proposed are generalization by pruning and generalization by replacement. Fusheng Wang et al [4] have proposed two methods for RFID data filtering. They are i) Low level data filtering ii) Semantic data filtering.…”

Section: Filteringmentioning

confidence: 99%

Heuristic Event Filtering Methodology for Interval based Temporal Semantics

Govindasamy¹,

Thambidurai²

2013

IJCA

View full text Add to dashboard Cite

“…Pattern queries only contain in-place conditions, i.e., the query qualification is either based on the attributes of events matched in the input stream [8,12,16,17] or on static information pre-loaded once yet not updated during query execu- tion [1,4,15]. Moreover, reactions for event detections are limited to "side-effect-free" actions like sending a message or logging events that do not affect the event detection in turn [22]. Supporting concurrent update actions within the continuous execution of pattern queries over streams, especially actions that directly affect the pattern query results themselves, is an open problem.…”

Section: Umms-wpi Ccts Collaborative Grantmentioning

confidence: 99%

“…ADDITIONAL RELATED WORK [22] presents a methodology to define the reactions for RFID event detection. But it only deals with "trivial" reactions like sending a message or logging events, that do not affect the event detection in turn.…”

Section: G2 Performance Metricsmentioning

confidence: 99%

See 1 more Smart Citation

Active complex event processing over event streams

2011

View full text Add to dashboard Cite

State-of-the-art Complex Event Processing technology (CEP), while effective for pattern query execution, is limited in its capability of reacting to opportunities and risks detected by pattern queries. Especially reactions that affect the query results in turn have not been addressed in the literature. We propose to tackle these unsolved problems by embedding active rule support within the CEP engine, henceforth called Active CEP (ACEP). Active rules in ACEP allow us to specify a pattern query's dynamic condition and real-time actions. The technical challenge is to handle interactions between queries and reactions to queries in the high-volume stream execution. We hence introduce a novel stream-oriented transactional model along with a family of stream transaction scheduling algorithms that ensure the correctness of concurrent stream execution. We demonstrate the power of ACEP technology by applying it to the development of a healthcare system being deployed in UMass Medical School hospital. Through extensive performance experiments using real data streams, we show that our unique Low-Water-Mark stream transaction scheduler, customized for streaming environments, successfully achieves near-realtime system responsiveness and gives orders-of-magnitude better throughput than our alternative schedulers.

show abstract

Complex RFID event processing

Cited by 86 publications

References 25 publications

A Research of Sensors Complementary for the RFID Wireless Network based on the Variable Coverage Radius

A Research of Sensors Complementary for the RFID Wireless Network based on the Variable Coverage Radius

Heuristic Event Filtering Methodology for Interval based Temporal Semantics

Active complex event processing over event streams

Contact Info

Product

Resources

About