IMT Institutional Repository: No conditions. Results ordered -Date Deposited. 2024-03-29T14:58:48ZEPrintshttp://eprints.imtlucca.it/images/logowhite.pnghttp://eprints.imtlucca.it/2013-05-17T13:45:01Z2013-09-03T08:26:04Zhttp://eprints.imtlucca.it/id/eprint/1588This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/15882013-05-17T13:45:01ZSPoT: Representing the Social, Spatial, and Temporal
Dimensions of Human Mobility with a Unifying FrameworkModeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As
a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a exible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility. Our framework, named SPoT, is able to incorporate the three dimensions - spatial, social, and temporal - of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the exibility of the framework, and we show that SPoT is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge.Dmytro Karamshukdmytro.karamshuk@imtlucca.itChiara BoldriniMarco ContiAndrea Passarella2013-04-30T14:12:58Z2013-04-30T14:12:58Zhttp://eprints.imtlucca.it/id/eprint/1557This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/15572013-04-30T14:12:58ZAn arrival-based framework for human mobility modelingModeling human mobility is crucial in the performance analysis and simulation of mobile ad hoc networks, where contacts are exploited as opportunities for peer-to-peer message forwarding. The current approach to human mobility modeling has been based on continuously modifying models, trying to embed in them the newest features of mobility properties (e.g., visiting patterns to locations or inter-contact times) as they came up from trace analysis. As a consequence, typically these models are neither flexible (i.e., features of mobility cannot be changed without changing the model) nor controllable (i.e., the exact shape of mobility properties cannot be controlled directly). In order to take into account the above requirements, in this paper we propose a mobility framework whose goal is, starting from the stochastic process describing the arrival patterns of users to locations, to generate pairwise inter-contact times and aggregate inter-contact times featuring a predictable probability distribution. We validate the proposed framework by means of simulations. In addition, assuming that the arrival process of users to locations can be described by a Bernoulli process, we mathematically derive a closed form for the pairwise and aggregate inter-contact times, proving the controllability of the proposed approach in this case.Dmytro Karamshukdmytro.karamshuk@imtlucca.itChiara BoldriniMarco ContiAndrea Passarella2013-04-30T13:43:46Z2013-04-30T13:44:36Zhttp://eprints.imtlucca.it/id/eprint/1556This item is in the repository with the URL: http://eprints.imtlucca.it/id/eprint/15562013-04-30T13:43:46ZHuman mobility models for opportunistic networksMobile ad hoc networks enable communications between clouds of mobile devices without the need for a preexisting infrastructure. One of their most interesting evolutions are opportunistic networks, whose goal is to also enable communication in disconnected environments, where the general absence of an end-to-end path between the sender and the receiver impairs communication when legacy MANET networking protocols are used. The key idea of OppNets is that the mobility of nodes helps the delivery of messages, because it may connect, asynchronously in time, otherwise disconnected subnetworks. This is especially true for networks whose nodes are mobile devices (e.g., smartphones and tablets) carried by human users, which is the typical OppNets scenario. In such a network where the movements of the communicating devices mirror those of their owners, finding a route between two disconnected devices implies uncovering habits in human movements and patterns in their connectivity (frequencies of meetings, average duration of a contact, etc.), and exploiting them to predict future encounters. Therefore, there is a challenge in studying human mobility, specifically in its application to OppNets research. In this article we review the state of the art in the field of human mobility analysis and present a survey of mobility models. We start by reviewing the most considerable findings regarding the nature of human movements, which we classify along the spatial, temporal, and social dimensions of mobility. We discuss the shortcomings of the existing knowledge about human movements and extend it with the notion of predictability and patterns. We then survey existing approaches to mobility modeling and fit them into a taxonomy that provides the basis for a discussion on open problems and further directions for research on modeling human mobility.Dmytro Karamshukdmytro.karamshuk@imtlucca.itChiara BoldriniMarco ContiAndrea Passarella