124,316 research outputs found

    Mobility modeling and management for next generation wireless networks

    Get PDF
    Mobility modeling and management in wireless networks are the set of tasks performed in order to model motion patterns, predict trajectories, get information on mobiles\u27 whereabouts and to make use of this information in handoff, routing, location management, resource allocation and other functions. In the literature, the speed of mobile is often and misleadingly referred to as the level of mobility, such as high or low mobility. This dissertation presents an information theoretic approach to mobility modeling and management, in which mobility is considered as a measure of uncertainty in mobile\u27s trajectory, that is, the mobility is low if the trajectory of a mobile is highly predictable even if the mobile is moving with high speed. On the other hand, the mobility is high if the trajectory of the mobile is highly erratic. Based on this mobility modeling concept, we classify mobiles into predictable and non-predictable mobility classes and optimize network operations for each mobility class. The dynamic mobility classification technique is applied to various mobility related issues of the next generation wireless networks such as location management, location-based services, and energy efficient routing in multihop cellular networks

    Breaking the habit: measuring and predicting departures from routine in individual human mobility

    No full text
    Researchers studying daily life mobility patterns have recently shown that humans are typically highly predictable in their movements. However, no existing work has examined the boundaries of this predictability, where human behaviour transitions temporarily from routine patterns to highly unpredictable states. To address this shortcoming, we tackle two interrelated challenges. First, we develop a novel information-theoretic metric, called instantaneous entropy, to analyse an individual’s mobility patterns and identify temporary departures from routine. Second, to predict such departures in the future, we propose the first Bayesian framework that explicitly models breaks from routine, showing that it outperforms current state-of-the-art predictor

    Coupling Human Mobility and Social Ties

    Get PDF
    Studies using massive, passively data collected from communication technologies have revealed many ubiquitous aspects of social networks, helping us understand and model social media, information diffusion, and organizational dynamics. More recently, these data have come tagged with geographic information, enabling studies of human mobility patterns and the science of cities. We combine these two pursuits and uncover reproducible mobility patterns amongst social contacts. First, we introduce measures of mobility similarity and predictability and measure them for populations of users in three large urban areas. We find individuals' visitations patterns are far more similar to and predictable by social contacts than strangers and that these measures are positively correlated with tie strength. Unsupervised clustering of hourly variations in mobility similarity identifies three categories of social ties and suggests geography is an important feature to contextualize social relationships. We find that the composition of a user's ego network in terms of the type of contacts they keep is correlated with mobility behavior. Finally, we extend a popular mobility model to include movement choices based on social contacts and compare it's ability to reproduce empirical measurements with two additional models of mobility

    Throughput Maximization for Mobile Relaying Systems

    Full text link
    This paper studies a novel mobile relaying technique, where relays of high mobility are employed to assist the communications from source to destination. By exploiting the predictable channel variations introduced by relay mobility, we study the throughput maximization problem in a mobile relaying system via dynamic rate and power allocations at the source and relay. An optimization problem is formulated for a finite time horizon, subject to an information-causality constraint, which results from the data buffering employed at the relay. It is found that the optimal power allocations across the different time slots follow a "stair-case" water filling (WF) structure, with non-increasing and non-decreasing water levels at the source and relay, respectively. For the special case where the relay moves unidirectionally from source to destination, the optimal power allocations reduce to the conventional WF with constant water levels. Numerical results show that with appropriate trajectory design, mobile relaying is able to achieve tremendous throughput gain over the conventional static relaying.Comment: submitted for possible conference publicatio

    Patterns of Individual Shopping Behavior

    Get PDF
    Much of economic theory is built on observations of aggregate, rather than individual, behavior. Here, we present novel findings on human shopping patterns at the resolution of a single purchase. Our results suggest that much of our seemingly elective activity is actually driven by simple routines. While the interleaving of shopping events creates randomness at the small scale, on the whole consumer behavior is largely predictable. We also examine income-dependent differences in how people shop, and find that wealthy individuals are more likely to bundle shopping trips. These results validate previous work on mobility from cell phone data, while describing the unpredictability of behavior at higher resolution.Comment: 4 pages, 5 figure
    • …
    corecore