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Sampling Distributed Schedulers for Resilient Space Communication

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NASA Formal Methods (NFM 2020)

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Abstract

We consider routing in delay-tolerant networks like satellite constellations with known but intermittent contacts, random message loss, and resource-constrained nodes. Using a Markov decision process model, we seek a forwarding strategy that maximises the probability of delivering a message given a bound on the network-wide number of message copies. Standard probabilistic model checking would compute strategies that use global information, which are not implementable since nodes can only act on local data. In this paper, we propose notions of distributed schedulers and good-for-distributed-scheduling models to formally describe an implementable and practically desirable class of strategies. The schedulers consist of one sub-scheduler per node whose input is limited to local information; good models additionally render the ordering of independent steps irrelevant. We adapt the lightweight scheduler sampling technique in statistical model checking to work for distributed schedulers and evaluate the approach, implemented in the Modest Toolset, on a realistic satellite constellation and contact plan.

The authors are listed alphabetically. This work was supported by ANPCyT PICT-2017-3894 (RAFTSys), ERC grant 695614 (POWVER), NWO VENI grant no. 639.021.754, and SeCyT project 33620180100354CB (ARES).

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Notes

  1. 1.

    The abstraction underapproximates contacts (it may only remove or shorten communication opportunities), so a strategy for the abstract plan is always implementable.

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Author information

Authors and Affiliations

  1. CONICET, Córdoba, Argentina

    Pedro R. D’Argenio & Juan A. Fraire

  2. Saarland University, Saarbrücken, Germany

    Pedro R. D’Argenio & Juan A. Fraire

  3. Universidad Nacional de Córdoba, Córdoba, Argentina

    Pedro R. D’Argenio & Juan A. Fraire

  4. University of Twente, Enschede, The Netherlands

    Arnd Hartmanns

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  1. Pedro R. D’Argenio
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  2. Juan A. Fraire
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  3. Arnd Hartmanns
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Correspondence to Arnd Hartmanns .

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  1. NASA Ames Research Center, Moffett Field, CA, USA

    Ritchie Lee

  2. SRI International, Menlo Park, CA, USA

    Susmit Jha

  3. KBR Inc., NASA Ames Research Center, Moffett Field, CA, USA

    Anastasia Mavridou

  4. NASA Ames Research Center, Moffett Field, CA, USA

    Dimitra Giannakopoulou

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D’Argenio, P.R., Fraire, J.A., Hartmanns, A. (2020). Sampling Distributed Schedulers for Resilient Space Communication. In: Lee, R., Jha, S., Mavridou, A., Giannakopoulou, D. (eds) NASA Formal Methods. NFM 2020. Lecture Notes in Computer Science(), vol 12229. Springer, Cham. https://doi.org/10.1007/978-3-030-55754-6_17

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