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A fuzzy-decision based approach for Composite event detection in wireless sensor networks.
Shukui Zhang1, Hao Chen2, Qiaoming Zhu2
1School of Computer Science and Technology, Soochow University, Suzhou 215006, China ; State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China.
Thescientificworldjournal
|August 20, 2014
Summary
This study introduces a new method for composite event detection in wireless sensor networks (WSNs). The proposed algorithm enhances accuracy and reduces traffic by effectively filtering faulty data and using fuzzy logic for event judgment.
Area of Science:
- Computer Science
- Network Engineering
- Artificial Intelligence
Background:
- Event detection is crucial in wireless sensor networks (WSNs).
- Composite events, reflecting multiple properties, offer a more realistic approach to event status.
- Existing methods face challenges with data unreliability and fuzzy event definitions.
Purpose of the Study:
- To propose a criterion for determining composite event areas.
- To develop a dominating set-based network topology construction algorithm for random deployments.
- To introduce a cluster-based two-dimensional τ-GAS algorithm and a fuzzy-decision based composite event decision mechanism.
Main Methods:
- Analysis of composite event characteristics.
- Development of a network topology construction algorithm using dominating sets.
- Implementation of a two-dimensional τ-GAS algorithm for data filtering.
- Application of a fuzzy-decision mechanism for composite event judgment.
Main Results:
- The two-dimensional τ-GAS algorithm effectively filters fault node data, reducing the influence of erroneous data.
- The fuzzy-decision based composite event judgment mechanism offers advantages over fuzzy-logic algorithms with lower computational complexity.
- The proposed algorithm improves detection accuracy and reduces network traffic compared to CollECT and CDS algorithms.
Conclusions:
- The developed algorithms provide a robust solution for composite event detection in WSNs.
- The approach effectively handles data unreliability and fuzzy event definitions.
- The proposed methods enhance WSN performance in terms of accuracy and efficiency.
