Abstract
Transformations from shared memory model to wireless sensor networks (WSNs) quickly become inefficient in the presence of prevalent message losses in WSNs, and this prohibits their wider adoption. To address this problem, we propose a variation of the shared memory model, the SF shared memory model, where the actions of each node are partitioned into slow actions and fast actions. The traditional shared memory model consists only of fast actions and a lost message can disable the nodes from execution. Slow actions, on the other hand, enable the nodes to use slightly stale state from other nodes, so a message loss does not prevent the nodes from execution. We quantify over the advantages of using slow actions under environments with varying message loss probabilities, and find that a slow action has asymptotically better chance of getting executed than a fast action when the message loss probability increases. We also present guidelines for helping the protocol designer identify which actions can be marked as slow so as to enable the transformed program to be more loosely-coupled, and tolerate communication problems (latency, loss) better.
This work was partially sponsored by NSF CNS 0914913, NSF 0916504, and Air Force Contract FA9550-10-1-0178.
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References
Arora, A.: Efficient reconfiguration of trees: A case study in the methodical design of nonmasking fault-tolerance. Science of Computer Programming (1996)
Arumugam, M.: A distributed and deterministic TDMA algorithm for write-all-with-collision model. In: Kulkarni, S., Schiper, A. (eds.) SSS 2008. LNCS, vol. 5340, pp. 4–18. Springer, Heidelberg (2008)
Arumugam, M., Kulkarni, S.S.: Self-stabilizing deterministic time division multiple access for sensor networks. AIAA Journal of Aerospace Computing, Information, and Communication (JACIC) 3, 403–419 (2006)
Dijkstra, E.W.: Self-stabilizing systems in spite of distributed control. Communications of the ACM 17(11) (1974)
Dolev, S., Israeli, A., Moran, S.: Self-stabilization of dynamic systems assuming only read/write atomicity. Distributed Computing 7, 3–16 (1993)
Herman, T.: Models of self-stabilization and sensor networks. In: Das, S.R., Das, S.K. (eds.) IWDC 2003. LNCS, vol. 2918, pp. 205–214. Springer, Heidelberg (2003)
Kulkarni, S.S., Arumugam, M.: SS-TDMA: A self-stabilizing mac for sensor networks. In: Sensor Network Operations. Wiley/IEEE Press (2006)
Kulkarni, S.S., Arumugam, M.: Transformations for write-all-with-collision model. Computer Communications 29(2), 183–199 (2006)
Mizuno, M., Nesterenko, M.: A transformation of self-stabilizing serial model programs for asynchronous parallel computing environments. Information Processing Letters 66(6), 285–290 (1998)
Nesterenko, M., Arora, A.: Stabilization-preserving atomicity refinement. Journal of Parallel and Distributed Computing 62(5), 766–791 (2002)
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Arumugam, M., Demirbas, M., Kulkarni, S.S. (2010). “Slow Is Fast” for Wireless Sensor Networks in the Presence of Message Losses. In: Dolev, S., Cobb, J., Fischer, M., Yung, M. (eds) Stabilization, Safety, and Security of Distributed Systems. SSS 2010. Lecture Notes in Computer Science, vol 6366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16023-3_16
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DOI: https://doi.org/10.1007/978-3-642-16023-3_16
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