Self-stabilization by local checking and correction (extended abstract)
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
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ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Efficient tracing of failed nodes in sensor networks
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Synopsis diffusion for robust aggregation in sensor networks
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Sympathy for the sensor network debugger
Proceedings of the 3rd international conference on Embedded networked sensor systems
Analyzing the Yield of ExScal, a Large-Scale Wireless Sensor Network Experiment
ICNP '05 Proceedings of the 13TH IEEE International Conference on Network Protocols
Kansei: A High-Fidelity Sensing Testbed
IEEE Internet Computing
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IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Snap-Stabilizing PIF and Useless Computations
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
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Wireless sensor networks (WSNs) comprised of low-cost devices tend to be unreliable, with failures a common phenomenon. Being able to accurately observe the network health status -- of nodes of each type and links of each type -- is essential to properly configure applications on WSN fabrics and to interpret the information collected from them. In this paper we study accurate network health monitoring in WSNs. Specifically, we reconsider the well-known problem of message-passing rooted spanning tree construction and its use in PIF (propagation of information with feedback) for the case of a WSN. We present a stabilizing protocol, Chowkidar, that is initiated upon demand; that is, it does not involve ongoing maintenance, and it terminates with accurate results, including detection of failure and restart during the monitoring process. Our protocol is distinguished from others in two important ways. Given the resource constraints of WSNs, it is message-efficient in that it uses only a few messages per node. And it tolerates ongoing node and link failure and node restart, in contrast to requiring that faults stop during convergence. We have implemented the protocol as part of enabling a network health status service that is tightly integrated with a remotely accessible wireless sensor network testbed, Kansei, at The Ohio State University. We report on experimental results.