Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
The Redwood Project [distributed information system]
COMPCON '95 Proceedings of the 40th IEEE Computer Society International Conference
Fault Tolerance in Collaborative Sensor Networks for Target Detection
IEEE Transactions on Computers
IEEE Transactions on Computers
TIBFIT: Trust Index Based Fault Tolerance for Arbitrary Data Faults in Sensor Networks
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
On Distributed Fault-Tolerant Detection in Wireless Sensor Networks
IEEE Transactions on Computers
Eco: Ultra-Wearable and Expandable Wireless Sensor Platform
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
SASHA: toward a self-healing hybrid sensor network architecture
EmNets '05 Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors
Efficient and fault-tolerant feature extraction in wireless sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
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In order to provide efficient and suitable services for users in a ubiquitous computing environment, many kinds of context information technologies have been researched. Wireless sensor networks are among the most popular technologies providing such information. Therefore, it is very important to guarantee the reliability of sensor data gathered from wireless sensor networks. However, there are several factors associated with faulty sensor readings which make sensor readings unreliable. In this paper, we classify faulty sensor readings into sensor faults and measurement errors, then propose a novel in-network data verification algorithm which includes adaptive fault checking, measurement error elimination and data refinement. The proposed algorithm eliminates faulty readings as well as refines normal sensor readings, to increase reliability. Also, to achieve scalability of sensor networks and minimize network overhead, the proposed scheme involves a distributed implementation in a local area. The simulation study shows that the in-network data verification algorithm is highly reliable and its network overhead is very low compared to previous works. Reliability and overhead is improved by a maximum of 10---30% and 70%, respectively.