Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
A group mobility model for ad hoc wireless networks
MSWiM '99 Proceedings of the 2nd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
ANEJOS: a java based simulator for ad hoc networks
Future Generation Computer Systems
Modeling mobility for vehicular ad-hoc networks
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
JiST: an efficient approach to simulation using virtual machines: Research Articles
Software—Practice & Experience
Access and mobility of wireless PDA users
ACM SIGMOBILE Mobile Computing and Communications Review
An integrated mobility and traffic model for vehicular wireless networks
Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks
A community based mobility model for ad hoc network research
REALMAN '06 Proceedings of the 2nd international workshop on Multi-hop ad hoc networks: from theory to reality
Real-world environment models for mobile network evaluation
IEEE Journal on Selected Areas in Communications
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Mobility models must scale accordingly to the application and reflect real scenarios in which wireless devices are deployed. Typical examples of scenarios requiring precise mobility models are critical situations (e.g., vehicular traffic incident, escaping pedestrians in emergency situations) – for which the ad hoc paradigm was first designed for. In these particular situations, autonomous agents of communicating devices will assist mobile users in their displacements either to avoid traffic jam due to incidents or find the closest emergency exit. But, since the environment conditions (i.e., flow of pedestrians or vehicles and incidents) may change during time in part due to mobility itself, autonomous agents assisting mobile users in their displacements must constantly exchange information and dynamically adapt to the perceived situations. This requires to precisely modeling both mobility (vehicular and pedestrian traffic) and communications systems between agents. Unfortunately, these two areas have been treated separately, although mobility and network simulators should be tightly bound. In this paper, we propose a new modeling approach to mobility, namely Behavioral Mobility models (BM), which decomposes mobility into simple atomic individual behaviors. Combined, these behaviors yield realistic displacement patterns by reproducing the mobility observed at small scales in every day life, in both space and time. We also propose to bind mobility and network simulators to run joint simulations in order to push simulations to more realness. This approach combined to BM models is particularly suited to simulate critical situations where mobility is influenced by the changing environment conditions. We demonstrate the feasibility of our approach with two cases studies.