Packet forwarding in pocket switched networks -an empirical characterization of human mobility

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Abstract

Pocket switched networks (PSNs) make use of human mobility and local forwarding in order to distribute data. Information can be stored and passed, taking advantage of the device mobility, or forwarded over a wireless link when an appropriate contact is met. Such networks fall into the fields of mobile ad-hoc networking and delay-tolerant networking. PSN are totally distributed and cannot rely on central services for issues such as naming, authentication, trustatibility. The direct consequence is that forwarding in PSN is non trivial. In order to better understand the challenges associated to PSN design, we have collected human mobility data. We establish three fundamental properties of PSNs. First, the distribution of inter-contact time follows an approximate power law over a large time range in all data sets. This observation is at odds with the exponential decay expected by many currently used mobility models. Second, we establish that the diameter of PSNs is in the order of 10 hops, confirming the existence of the well know "small world" phenomenon in human mobility. Last, we show that all forwarding algorithms are equivalent from a delay and success rate standpoint due to a "path explosion" phenomenon that generally occurs a coupe of minute after the optimal path. We establish these three properties experimentally and give in each case a simple analytical model that explains our observations. We discuss the implications of these observations on forwarding algorithms in PSN. We conclude the talk by early results on the role of communities and interest in the PSN node population. These communities could be later used to optimize packet forwarding. We describe the on-going implementation of our PSN application. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Diot, C. (2007). Packet forwarding in pocket switched networks -an empirical characterization of human mobility. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4866 LNCS, p. 1). Springer Verlag. https://doi.org/10.1007/978-3-540-76809-8_1

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