Please use this identifier to cite or link to this item: https://doi.org/10.1109/DS-RT.2006.16
Title: EGRESS: Environment for generating realistic scenarios for simulations
Authors: Sridhar, K.N.
Hao, S.
Chan, M.C. 
Ananda, A.L. 
Issue Date: 2006
Source: Sridhar, K.N.,Hao, S.,Chan, M.C.,Ananda, A.L. (2006). EGRESS: Environment for generating realistic scenarios for simulations. Proceedings - IEEE International Symposium on Distributed Simulation and Real-Time Applications, DS-RT : 15-22. ScholarBank@NUS Repository. https://doi.org/10.1109/DS-RT.2006.16
Abstract: In MANETs, majority of performance studies are carried out via simulations, where node mobility and radio propagation models play a crucial role. However, popular simulation tools, like NS-2 [1] and GloMoSim [2], use simplistic random mobility patterns and free space radio propagation models. Such simplification ignores many crucial details in environment where movements are not random and obstacles are common. To have a better understanding of MANET protocols, there is a need for a tool that can generate more realistic mobility scenarios and provide better radio propagation model. This paper presents EGRESS, which is built on top of NS-2 and consists of two major components: SGT and ORPM. SGT is a tool that generates node movements in an urban environment with buildings and pathways. ORPM is an obstructive radio propagation model, which enhances the existing radio models in NS-2 by taking into account obstacles in a 3D environment. We believe EGRESS is the first open source tool that provides such integrated and more realistic features for simulating urban environment. Our simulation results show that using more realistic scenarios can have a significant impact on network topology and performance of routing protocols. © 2006 IEEE.
Source Title: Proceedings - IEEE International Symposium on Distributed Simulation and Real-Time Applications, DS-RT
URI: http://scholarbank.nus.edu.sg/handle/10635/42088
ISBN: 0769526977
ISSN: 15506525
DOI: 10.1109/DS-RT.2006.16
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