On the Symmetry of Userobility in Wireless Networks
Bruno Astuto, Katia Obraczka · 2011
�bstract— In this paper analyzed WLAN-� GPS-� and traces that record mobility in a variety of network environments. We observe that from a macroscopic levelhuman mobility is symmetric. In other wordsthe number of users that move from pointto point B approximates the number of users that go in the opposite directioni.e.� from B to �. We show that this type of symmetry is more accentuated in mobility modelsin particularin random way-point mobility. We also study the direction of movement which also exhibits symmetric behavior in both real- as well as mobility. Additional contributions of our work include metrics to quantify mobility symmetry. We conclude the paper with a discussion of possible applications of our results in mobile networking. IIntroduction Node mobility is a key factor in the design and perfor- mance evaluation of mobile networks and their protocols and mobility characterization has attracted consider- able attention from the networking research community. Evaluation studies of early mobile networks and their protocols used most of the time synthetic mobility models such as random walk, Brownian motion, and the random way-point (RWP) model (1), just to mention a few. The RWP, in particular, has been one of the most used mobility models for evaluating mobile networks which motivated several studies that scrutinized its be- havior, identified a number of undesirable features (2), as well as proposed variations to improve its behavior. More recently, motivated in part by the problems associated with the RWP and recognizing the impor- tance of employing more realistic mobility scenarios when designing and evaluating mobile networks, there has been considerable interest in using real mobility traces and developing models that reflect real mobility. Crawdad (3), is an example of an initiative to make real mobility traces widely available to network researchers. In this paper, also motivated by the trend towards employing real mobility to design and evaluate wireless networks, we study different types of traces obtained by recording user mobility. Our goal is to identify patterns, extract features, and define metrics to characterize the spatial behavior of human mobility. As a result, we