Sensor failure detection and recovery mechanism based on support vector and genetic algorithm

The main role of wireless sensor networks is to collect environmental data. As the sensor nodes are vulnerable and work in unpredictable environments, sensors are possible to fail and return unexpected response. Therefore, fault detection and recovery are important in wireless sensor networks. In th...

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Bibliographic Details
Main Authors: Jiehui Zhu, Yang Yang, Xuesong Qiu, Zhipeng Gao
Format: Conference Proceeding
Language:English
Subjects:
Biological cells
Clustering algorithms
credibility level
Fault detection
fault recovery
genetic algorithm
Prediction algorithms
Routing
Support vector machines
support vector regression
Wireless sensor networks
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Summary:The main role of wireless sensor networks is to collect environmental data. As the sensor nodes are vulnerable and work in unpredictable environments, sensors are possible to fail and return unexpected response. Therefore, fault detection and recovery are important in wireless sensor networks. In this paper, we propose a fault detection algorithm based on support vector regression, which predicts the measurements of sensor nodes by using historical data. Credit levels of sensor nodes will be determined by a contrast between predictions and actual measured values. In this paper we also propose a fault recovery algorithm according to the node credit levels combined with genetic algorithm. The simulation results demonstrate that the algorithms we propose work well in failure detection rate, fault recovery speed and energy consumption.
DOI:10.1109/APNOMS.2014.6996565