SPoT: Representing the Social, Spatial, and Temporal Dimensions of Human Mobility with a Unifying Framework

Modeling 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

The stability region of the delay in Pareto opportunistic networks

The intermeeting time, i.e., the time between two consecutive contacts between a pair of nodes, plays a fundamental role in the delay of messages in opportunistic networks. A desirable property of message delay is that its expectation is finite, so that the performance of the system can be predicted. Unfortunately, when intermeeting times feature a Pareto distribution, this property does not always hold. In this paper, assuming heterogeneous mobility and Pareto intermeeting times, we provide a detailed analysis of the conditions for the expectation of message delay to be finite (i.e., to converge) when social-oblivious or social-aware forwarding schemes are used. More specifically, we consider different classes of social-oblivious and social-aware schemes, based on the number of hops allowed and the number of copies generated. Our main finding is that, in terms of convergence, allowing more than two hops may provide advantages only in the social-aware case. At the same time, we show that using a multi-copy scheme can in general improve the convergence of the expected delay. We also compare social-oblivious and social-aware strategies from the convergence standpoint and we prove that, depending on the mobility scenario considered, social-aware schemes may achieve convergence while social-oblivious cannot, and vice versa. Finally, we apply the derived convergence conditions to three popular contact data sets available in the literature (Cambridge, Infocom, and RollerNet), assessing the convergence of each class of forwarding protocols in these three cases

The sociable traveller: human travelling patterns in social-based mobility

Understanding how humans move is a key factor for the design and evaluation of networking protocols and mobility management solutions in mobile networks. This is particularly true for mobile scenarios in which conventional singlehop access to the infrastructure is not always possible, and multi-hop wireless forwarding is a must. We specifically focus on one of the most recent mobile networking paradigms, i.e., opportunistic networks. In this paradigm the communication takes place directly between the personal devices (e.g., smartphones and PDAs) that the users carry with them during their daily activities, without any assumption about pre-existing infrastructures. Among all mobility characteristics that may affect the performance of opportunistic networks, the users\u27 travelling patterns have recently gained a lot of attention due to their impact on the spreading of both viruses and messages in such a network. In this paper we consider a social-based mobility model (HCMM) and we extend this model to account for the typical travelling behaviour of users. To the best of our knowledge, the resulting mobility model is the first model in which movements driven by social relations also match statistical features of travelling patterns as measured in reality. Finally, we evaluate our proposal through simulations over a wide range of scenarios, emphasizing the effect of finite sampling on the obtained results

Performance modelling of opportunistic forwarding with exact knowledge

The Delay Tolerant Networking paradigm aims to enable communications in disconnected environments where traditional protocols would fail. Opportunistic networks are delay tolerant networks whose nodes are typically the users\u27 personal mobile devices. Communications in an opportunistic network rely on the mobility of users: each message is forwarded from node to node, according to a hop-by-hop decision process that selects the node that is better suited for bringing the message closer to its destination. Despite the variety of forwarding protocols that have been proposed in the recent years, there is no reference framework for the performance modelling of opportunistic forwarding. In this paper we start to fill this gap by proposing an analytical model for the expected delay and the expected number of hops experienced by messages when delivered in an opportunistic fashion. This model seamlessly integrates both social-aware and social-oblivious single-copy forwarding protocols, as well as different hypotheses for user contact dynamics. The proposed framework is used to derive bounds on the expected delay under homogeneous and heterogeneous contact patterns. We found that, in heterogeneous settings, finite expected delay can be guaranteed not only when nodes\u27 inter-meeting times follow an exponential or power law with exponential cut-off distribution, but also when they are power law distributed, as long as weaker conditions than those derived by Chaintreau et al. [1] for the homogeneous scenario are satisfied

Context and resource awareness in opportunistic network data dissemination

Opportunistic networks are challenging mobile ad hoc networks characterised by frequent disconnections and partitioning. In this paper we focus on data-dissemination services, i.e. cases in which data should be disseminated in the network without a priori knowledge about the set of intended destinations. We propose a general autonomic datadissemination framework that exploits information about the users\u27 context and social behaviour, to decide how to replicate and replace data on nodes\u27 buffers. Furthermore, our data-dissemination scheme explicitly takes into account resource constraints, by jointly considering the expected utility of data replication and the associated costs. The results we present show that our solution is able to improve data availability, provide fairness among nodes, and reduce the network load with respect to reference proposals available in the literature

Modelling Data Dissemination in Opportunistic Networks

In opportunistic networks data dissemination is an impor- tant, although not widely explored, topic. Since oppor- tunistic networks topologies are very challenged and un- stable, data-centric approaches are an interesting direction to pursue. Data should be proactively and cooperatively disseminated from sources towards possibly interested re- ceivers, as sources and receivers might not be aware of each other, and never get in touch directly. In this paper we con- sider a utility-based cooperative data dissemination system in which the utility of data is defined based on the social relationships between users. Specifically, we study the per- formance of this system through an analytical model. Our model allows us to completely characterise the data dissem- ination process, as it describes both its stationary and tran- sient regimes. After validating the model, we study the sys- tem\u27s behaviour with respect to key parameters such as the definition of the data utility function, the initial data allo- cation on nodes, the number of users in the system, and the data popularity