A Continuous Query Index for Processing Queries on RFID Data Stream

2007 ◽  
Author(s):  
Jaekwan Park ◽  
Bonghee Hong ◽  
Chaehoon Ban
Keyword(s):  
Data Stream ◽  
Continuous Query ◽  
Rfid Data

A Continuous Query Processing System for RFID Data Stream

2013 ◽  
Vol 5 (8) ◽  
pp. 1282-1289
Author(s):  
Chang Hyun Park ◽  
Hyung Rim Choi ◽  
Byung Kwon Park ◽  
Young Jae Park
Keyword(s):  
Query Processing ◽  
Data Stream ◽  
Processing System ◽  
Continuous Query ◽  
Rfid Data ◽  
Continuous Query Processing

RFID data stream processing technology based on CEP

2009 ◽  
Vol 29 (10) ◽  
pp. 2786-2790 ◽  
Author(s):  
Xiao-jia YIN ◽  
Shi-guang JU ◽  
Ying-jie WANG
Keyword(s):  
Data Stream ◽  
Stream Processing ◽  
Processing Technology ◽  
Data Stream Processing ◽  
Rfid Data

scholarly journals Efficient Processing of ContinuousSkylineQuery over Smarter Traffic Data Stream for Cloud Computing

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Wang Hanning ◽  
Xu Weixiang ◽  
Jiulin Yang ◽  
Lili Wei ◽  
Jia Chaolong
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Data Stream ◽  
Sliding Window ◽  
Continuous Query ◽  
Traffic Data ◽  
Stream Data ◽  
Smart Transportation ◽  
Efficient Processing ◽  
Query Algorithm

The analyzing and processing of multisource real-time transportation data stream lay a foundation for the smart transportation's sensibility, interconnection, integration, and real-time decision making. Strong computing ability and valid mass data management mode provided by the cloud computing, is feasible for handlingSkylinecontinuous query in the mass distributed uncertain transportation data stream. In this paper, we gave architecture of layered smart transportation about data processing, and we formalized the description about continuous query over smart transportation dataSkyline. Besides, we proposedmMR-SUDSalgorithm (Skylinequery algorithm of uncertain transportation stream data based onmicro-batchinMap Reduce) based on sliding window division and architecture.

Complex Event Processing Mechanism in Internet of Things and its Application in Logistics

2012 ◽  
Vol 235 ◽  
pp. 309-313
Author(s):  
Chun Mei Wei
Keyword(s):  
Internet Of Things ◽  
Hierarchical Model ◽  
Data Stream ◽  
Semantic Information ◽  
Complex Event Processing ◽  
Business Logic ◽  
Event Handling ◽  
Rfid Data ◽  
Complex Events ◽  
Processing Mechanism

The data and events from Internet of Things are mass but their semantic information is very simple and can not be utilized in upper applications directly, so we have to analyze lots of data to find out useful business logic in these events. To aggregate these simple basic events into advanced events, a hierarchical model was designed to process RFID data stream, in which a complex events processing (CEP) mechanism was used to analyze atomic events in RFID data. We defined event handling operators in CEP mechanism to process business logics. As an example, the CEP was used in a logistic application, which implemented logistic events aggregation and complex events processing effectively. The result indicates the CEP mechanism is an effective approach to handle data and events in Internet of Things.

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