A structured group mobility model for the simulation of mobile ad hoc networks
Proceedings of the second international workshop on Mobility management & wireless access protocols
Characterizing mobility and network usage in a corporate wireless local-area network
Proceedings of the 1st international conference on Mobile systems, applications and services
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
Crossing over the bounded domain: from exponential to power-law inter-meeting time in MANET
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Power law and exponential decay of inter contact times between mobile devices
Proceedings of the 13th annual ACM international conference on Mobile computing and networking
Modelling mobility in disaster area scenarios
Proceedings of the 10th ACM Symposium on Modeling, analysis, and simulation of wireless and mobile systems
Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
Generic mobility simulation framework (GMSF)
Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models
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Modeling movements in office is useful for smart indoor ad hoc networks. People carrying PDA or cell phones can encounter others and in some cases are able to establish connections and transfer data between them. Currently, commonly used mobility models, such as Random Walk and Random Waypoint Model, do not capture the real movements in real life scenarios, especially in office environments where three typical patterns of heterogeneous behavior, i.e., entity movements, group movements and regular movements, often occur. In this paper we propose a novel mobility simulation framework based on behavior patterns for office environments. The base part is Simulation Time Controller, on which we model the structure of offices and define behavior patterns. In this paper we define three typical patterns of behavior to simulate the heterogeneous movements mentioned above.To simulate more real movements, people can add more patterns of behavior to this framework, which is the main motivation of our framework. We also derive theoretic results of hitting time, which determines the packet delivery delay in Delay Tolerant Networks. Simulation studies show our expressions have error always under 10%. And the staying ratio of our simulation, i.e., the ratio between the time people spend in main place and the total time, is close to the MIT real traces.