A community based mobility model for ad hoc network research

By Mirco Musolesi, Cecilia Mascolo. REALMAN '06, 2006

384 citations recorded by the source corpus.

Validation of mobile ad hoc network protocols relies almost exclusively on simulation. The value of the validation is, therefore, highly dependent on how realistic the movement models used in the simulations are. Since there is a very limited number of available real traces in the public domain, synthetic models for movement pattern generation must be used. However, most widely used models are currently very simplistic, their focus being ease of implementation rather than soundness of foundation. As a consequence, simulation results of protocols are often based on randomly generated movement patterns and, therefore, may differ considerably from those that can be obtained by deploying the system in real scenarios. Movement is strongly affected by the needs of humans to socialise or cooperate, in one form or another. Fortunately, humans are known to associate in particular ways that can be mathematically modelled and that have been studied in social sciences for years.In this paper we propose a new mobility model founded on social network theory. 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 then mapped to a topographical space, with movements influenced by the strength of social ties that may also change in time. We have validated our model with real traces by showing that the synthetic mobility traces are a very good approximation of human movement patterns.

Subfields: Computer Networks and Communications, Transportation

View Paper: https://www.semanticscholar.org/paper/efecaa920e8ea91d9422e4765860cb66b62581d3

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In Computer Networks and Communications

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Citations in the corpus

CAR: Context-Aware Adaptive Routing for Delay-Tolerant Mobile Networks (2009, methodology): “For this reason, we have used a mobility model based on social network theory, the Community-based mobility model [11], [24].”
Modeling Time-Variant User Mobility in Wireless Mobile Networks (2007, background): “The concept of community is also mentioned in [19].”
How Small Labels Create Big Improvements (2006, background): “[10] proposed community based mobility model for mobile ad hoc research.”
Mobility models for vehicular ad hoc networks: a survey and taxonomy (2009, methodology): “Although being related to human mobility, Musolesi et al. illustrated this approach in [10] by developing a synthetic mobility model based on social network theory, then validated it using real traces.”
Spray and Focus: Efficient Mobility-Assisted Routing for Heterogeneous and Correlated Mobility (2007, background): “Although such desirable mobility characteristics could, to an extend, be found in some applications like, for example, VANETs [6], [7], in many other scenarios, especially those involving human interactions, mobility is strongly correlated in both time and space [21]–[24].”
HiBOp: a History Based Routing Protocol for Opportunistic Networks (2007, methodology): “The number of nodes was set to 80, and the transmission range was set to 100m. Nodes moved according to the traces generated by Community based Mobility Model [6].”
On the Levy-Walk Nature of Human Mobility (2008, neutral): “As it is not the purpose of our paper to present TLW as an accurate mobility model, we do not attempt to study and compare the performance of TLW to many more sophisticated mobility models in the literature (e.g., [ 26 ]‐[28]).”