An Ingestion Based Analytics Framework for Complex Event Processing Engine in Internet of Things

2018 ◽  
pp. 266-281 ◽  
Author(s):  
Sanket Mishra ◽  
Mohit Jain ◽  
B. Siva Naga Sasank ◽  
Chittaranjan Hota
Keyword(s):  
Internet Of Things ◽  
Complex Event Processing ◽  
Event Processing ◽  
Processing Engine

scholarly journals A Universal Complex Event Processing Mechanism Based on Edge Computing for Internet of Things Real-Time Monitoring

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 101865-101878 ◽  
Author(s):  
Lina Lan ◽  
Ruisheng Shi ◽  
Bai Wang ◽  
Lei Zhang ◽  
Ning Jiang
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Complex Event Processing ◽  
Edge Computing ◽  
Event Processing ◽  
Real Time Monitoring ◽  
Processing Mechanism

scholarly journals An Intelligent Complex Event Processing withDNumbers under Fuzzy Environment

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Fuyuan Xiao
Keyword(s):  
Complex Event Processing ◽  
Event Processing ◽  
The Novel ◽  
Human Beings ◽  
Topsis Method ◽  
Fuzzy Environment ◽  
Novel Method ◽  
Efficient Matching ◽  
Processing Engine ◽  
Support Decision Making

Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless,Dnumbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method withDnumbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

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