Opportunistic data collection through delegation

Greg Bigwood 1 Aline Carneiro Viana 2 Mathias Boc 3 Marcelo Dias de Amorim 4
2 ASAP - As Scalable As Possible: foundations of large scale dynamic distributed systems
UR1 - Université de Rennes 1, Inria Saclay - Ile de France, INSA - Institut National des Sciences Appliquées, CNRS - Centre National de la Recherche Scientifique : UMR
4 NPA - Networks and Performance Analysis
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : We consider a collection system where collectors move around gathering information generated by data producers. In such a system, data may remain uncollected when the number of collectors is insufficient to cover the whole population of producers. Motivated by the observation that node encounters are sufficient to build a connected relationship graph, we propose to take advantage of the inherent interactions among nodes and transform some producers into delegates. With such an approach, collectors only need to meet delegates that, in turn, are responsible for gathering data from a subset of standard producers. We achieve this goal through two contributions. First, we investigate several delegation strategies based on the relative importance of nodes in their social interactions (i.e., the node centrality). Second, by considering a prediction strategy that estimates the likelihood of two nodes meeting each other, we investigate how the delegation strategies perform on predicted traces. We evaluate the delegation strategies both in terms of coverage and size of the delegation existing real mobility data sets. We observe that delegation strategies that rely on localized information perform as well as the ones that consider a complete view of the topology.
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Greg Bigwood, Aline Carneiro Viana, Mathias Boc, Marcelo Dias de Amorim. Opportunistic data collection through delegation. [Research Report] RR-7361, INRIA. 2010, pp.27. ⟨inria-00508273v2⟩

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