ACM Computing Surveys (CSUR)
Information Processing Letters
A self-stabilizing algorithm for minimum-depth search of graphs
Information Sciences: an International Journal
Self-stabilization
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Self-Stabilizing Minimum Spanning Tree Construction on Message-Passing Networks
DISC '01 Proceedings of the 15th International Conference on Distributed Computing
A Self-Stabilizing Distributed Algorithm for Minimal Total Domination in an Arbitrary System Graph
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
Algorithms for generic role assignment in wireless sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Information Processing Letters
Fault tolerance in wireless sensor networks through self-stabilisation
International Journal of Communication Networks and Distributed Systems
SSS '08 Proceedings of the 10th International Symposium on Stabilization, Safety, and Security of Distributed Systems
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Wireless sensor networks (WSNs) pose challenges not pre- sent in classical distributed systems: resource limitations, high failure rates, and ad hoc deployment. The lossy nature of wireless communication can lead to situations, where nodes lose synchrony and programs reach arbitrary states. Traditional approaches to fault tolerance like replication or global resets are not feasible. In this work, the concept of self-stabilization is applied to WSNs. The majority of self-stabilizing algorithms found in the literature is based on models not suitable for WSNs: shared memory model, central daemon scheduler, unique processor identifiers, and atomicity. This paper proposes problem-independent transformations for algorithms that stabilize under the central daemon scheduler such that they meet the demands of a WSN. The transformed algorithms use randomization and are probabilistically self-stabilizing. This work allows to utilize many known self-stabilizing algorithms in WSNs. The proposed transformations are evaluated using simulations and a real WSN.