作者: Mirco Musolesi , Stephen Hailes , Cecilia Mascolo
关键词: Probability distribution 、 Computer science 、 Credibility 、 Mobile ad hoc network 、 Space (commercial competition) 、 Host (network) 、 Mobility model 、 Artificial intelligence 、 Public domain 、 Soundness 、 Theoretical computer science
摘要: Almost all work on mobile ad hoc networks relies simulations, which, in turn, rely realistic movement models for their credibility. Since there is a total absence of data the public domain, synthetic pattern generation must be used and most widely are currently very simplistic, focus being ease implementation rather than soundness foundation. Whilst it would preferable to have that better reflect real users, impossible validate any model against data. However, lazy conclude from this equally likely invalid so will do.We note strongly affected by needs humans socialise one form or another. Fortunately, known associate particular ways can mathematically modelled, bias patterns. Thus, we propose new mobility founded social network theory, because has empirically been shown useful as means describing human relationships. In particular, allows collections hosts grouped together way based relationships among individuals. This grouping only then mapped topographical space, with topography biased strength tie.We discuss evaluate emergent properties generated networks. show mechanism influences probability distribution average degree (i.e., number neighbours host) simulated network.