![]() ![]() Pawlikowski, K., Jeong, H.-D.J., Lee, J.-S.R.: On credibility of simulation studies of telecommunication networks. of Computer Science, Dartmouth College (2004) ![]() Kotz, D., et al.: Experimental evaluation of wireless simulation assumptions. Conference on Mobile Computing and Networking (ACM MobiCom 2004), Philadelphia, USA, ACM Press, New York (2004) Güneş, M., Bouazizi, I.: From Biology to Technology: Demonstration Environment for the Ant Routing Algorithm for Mobile Ad-hoc Networks. This process is experimental and the keywords may be updated as the learning algorithm improves. These keywords were added by machine and not by the authors. The integration of these two techniques allows to create simulation setups that closely model reality. To achieve a realistic radio wave propagation model a ray tracing approach is used. Our approach consists of a zone-based mobility generator and a high accuracy radio wave propagation model.įor the mobility generation a wide variety of well understood random mobility models is combined with a graph based zone model, where each zone has its own mobility model. In this paper we introduce a framework which combines realistic mobility and radio wave propagation models. the performance of routing protocols changes with these models. Both have strong impact on the performance of mobile ad-hoc networks, e.g. Two main steps on the way to more realistic simulations of mobile ad-hoc networks are the introduction of realistic mobility and sophisticated radio wave propagation models. ![]()
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