Abstract
We propose distributed algorithms for sampling networks based on a new class of random walks that we call Centrifugal Random Walks (CRW). A CRW is a random walk that starts at a source and always moves away from it. We propose CRW algorithms for connected networks with arbitrary probability distributions, and for grids and networks with regular concentric connectivity with distance based distributions. All CRW sampling algorithms select a node with the exact probability distribution, do not need warm-up, and end in a number of hops bounded by the network diameter.
Work partially supported by Comunidad de Madrid (S2009TIC-1692) and Spanish MICINN (TEC2011-29688-C02-01). Thanks to Husain Ibraheem for useful suggestions.
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Sevilla, A., Mozo, A., Fernández Anta, A. (2012). Brief Announcement: Node Sampling Using Centrifugal Random Walks. In: Aguilera, M.K. (eds) Distributed Computing. DISC 2012. Lecture Notes in Computer Science, vol 7611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33651-5_37
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DOI: https://doi.org/10.1007/978-3-642-33651-5_37
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