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.
This model defines a process called sociostation, rendered by 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).
Almost all work on mobile ad hoc networks relies on simulations, which, in turn, rely on realistic movement models for their credibility. Since there is a total absence of realistic data in the public domain, synthetic models for movement pattern generation must be used and the most widely used models are currently very simplistic, the focus being ease of implementation rather than soundness of foundation. Whilst it would be preferable to have models that better reflect the movement of real users, it is currently impossible to validate any movement model against real data. However, it is lazy to conclude from this that all models are equally likely to be invalid so any will do. We note that movement is strongly affected by the needs of humans to socialize in one form or another.
Fortunately, humans are known to associate in particular ways that can be mathematically modeled, and that are likely to bias their movement patterns. Thus, we propose a new mobility model that is founded on social network theory, because this has empirically been shown to be useful as a means of describing human relationships. In particular, the model allows collections of hosts to be grouped together in a way that is based on social relationships among the individuals. This grouping is only then mapped to a topographical space, with topography biased by the strength of social tie. We discuss the implementation of this mobility model and we evaluate emergent properties of the generated networks.
We focus on the causes of mobility. Starting from established research in sociology, we propose SIMPS, a mobility model of human crowds with pedestrian motion.
We propose Sociological Interaction Mobility for Population, a mobility model aimed at pedestrian crowd motion that explores recent sociological findings driving human interactions:
(i) Each human has specific socialization needs, quantified by a target social interaction level, which corresponds to her personal status (e.g., age and social class.
(ii) Humans make acquaintances in order to meet their social interaction needs. We show that these two components can be translated into a coherent set of behaviors, called sociostation.
- Network Module
- Random Waypoint Model
- Interaction - Based Mobility Model
- Simulation Space