A mobility model based on mobile phone users is therefore likely to overestimate the number of people within a population that are traveling.
Nonetheless, it is expected that the SBDS, once established, will strengthen the capabilities of policy makers and practitioners to design, fulfill, monitor, and evaluate novel policies from data-driven evidence (e.g., derivation of optimal routes for overnight city buses based on mobile phone user data, networking of industry clusters across regions from firm-based transaction data).
In this paper, we present a framework for estimating trajectories of cellular networks users based on mobile network operator data.
In user centric optimization based on mobile caching networks, access delay, caching hit rate and caching failure probability are often chosen as significant metrics for optimization.
In Dynamic Hierarchical Mobile IP (DHMIP) [15], the location update messages to the HAs can be reduced by setting up hierarchy of FAs, where the level number of the hierarchy is dynamically adjusted based on each mobile user's up-to-date mobility and traffic load information.
Vizury, and other adtech startups are also betting on a growing base of mobile users in markets such as China, India and Japan.
In this paper, we propose a novel analytical framework for the analysis of the dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain.
The most salient feature of DrMoM is that the optimal home region size and local region size can be dynamically determined per mobile user based on mobility and service characteristics of individual mobile nodes to minimize the overall network cost incurred by location management and data packet delivery.
With HCS, node mobility is based on simulating 50 mobile users moving by foot, 30 by car, and 6 by trams in the streets of downtown Helsinki.
