Abstract-Assessing mobility in a thorough fashion is a crucial step toward more efficient mobile network design. Recent research on mobility has focused on two main points: analyzing models and studying their impact on data transport. These works investigate the consequences of mobility. In this paper, instead, we focus on the causes of mobility. Starting from established research in sociology, we propose SIMPS, a mobility model of human crowd motion. This model defines two complimentary behaviors, namely socialize and isolate, that regulate an individual with regard to her/his own sociability level. SIMPS leads to results that agree with scaling laws observed both in small-scale and large-scale human motion. Although our model defines only two simple individual behaviors, we observe many emerging collective behaviors (group formation/splitting, path formation, and evolution). To our knowledge, SIMPS is the first model in the networking community that tackles the roots governing mobility.
Research into wireless data networks with mobile nodes has mostly considered Mobile Ad Hoc Networks (or MANETs). In such networks, it is generally assumed that end-to-end, possibly multi-hop paths between node pairs exist most of the time. Routing protocols designed to operate in MANETs assume that these paths are formed by a set of wireless links that exist contemporaneously. Disruption or delay tolerant networks (DTNs) have received significant attention recently. Their primary distinction from MANETs is that in DTNs links on an end-to-end path may not exist contemporaneously and intermediate nodes may need to store data waiting for opportunities to transfer data towards its destination. We call such DTN paths space-time paths to distinguish them from contemporaneous space paths used in MANETs. We argue in this paper that MANETs are actually a special case of DTNs. Furthermore, DTNs are, in turn, a special case of disconnected networks where even spacetime paths do not exist. In this paper we consider the question of how to classify mobile and wireless networks with the goal of understanding what form of routing is most suitable for which network. We first develop a formal graph-theoretic classification of networks based on the theory of evolving graphs. We next develop a routing-aware classification that recognizes that the boundaries between network classes are not hard and are dependent on routing protocol parameters. This is followed by the development of algorithms that can be used to classify a network based on information regarding node contacts. Lastly, we apply these algorithms to a selected set of mobility models in order to illustrate how our classification approach can be used to provide insight into wireless and mobile network design and operation.
Abstract. There is an increasing consensus that existing mobility models, such as the well-known random walk or random waypoint models, are insufficient to represent real node mobility. In this paper, we discuss the need for a better characterization of natural mobility. Our contributions rely on recent advances of real-life network analysis and modelling, and in particular on the observation that natural networks behave on a scale-free basis. We devise then a novel mobility modelling approach that focuses on the behavioral aspect of individuals and the interactions between them. This fulfils a gap between individual and group mobility models. Our first results show a strong relevance of the scale-free distribution in mobility modelling, and open further directions in modelling the costs associated to building a network structure in general.
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