Human mobility in MANET disaster area simulation - a realistic approach

Aschenbruck, Nils; Frank, Matthias; Martini, Peter; Tölle, Jens

doi:10.1109/lcn.2004.64

Cited by 50 publications

(32 citation statements)

References 6 publications

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“…For example, [61] and [62] discuss an empirical model based on observations of pedestrians on a university campus, while [63] describes a realistic model of communication usage during disasters.…”

Section: Related Workmentioning

confidence: 99%

Realistic mobility simulation of urban mesh networks

2009

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It is a truism that today's simulations of mobile wireless networks are not realistic. In realistic simulations of urban networks, the mobility of vehicles and pedestrians is greatly influenced by the environment (e.g., the location of buildings) as well as by interaction with other nodes. For example, on a congested street or sidewalk, nodes cannot travel at their desired speed. Furthermore, the location of streets, sidewalks, hallways, etc. restricts the position of nodes, and traffic lights impact the flow of nodes. And finally, people do not wander the simulated region at random, rather, their mobility depends on whether the person is at work, at lunch, etc. In this paper, realistic simulation of mobility for urban wireless networks is addressed. In contrast to most other mobility modeling efforts, most of the aspects of the presented mobility model and model parameters are derived from surveys from urban planning and traffic engineering research. The mobility model discussed here is part of the UDel Models, a suite of tools for realistic simulation of urban wireless networks. The UDel Models simulation tools are available online.

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Section: Related Workmentioning

confidence: 99%

Realistic mobility simulation of urban mesh networks

2009

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“…Regarding the mobility of nodes, we have used the mobility generator BonnMotion [45] (we have used the version 2.0) which allows users to define a disaster response scenario [46][47] (the mobility model will be described in more details later on). With regard to the implementation of the proposed MOP, we have used the DEAP framework [48] which enables users to define a range of evolutionary algorithms in Python.…”

Section: Simulation Frameworkmentioning

confidence: 99%

“…The disaster area mobility model is based on a method called separation of the rooms [46] [47]. Using this method, the disaster scenario is divided into different context-based areas.…”

Section: Disaster Area Mobility Modelmentioning

confidence: 99%

“…The disaster mobility model used in the paper has already been used to model real disaster scenarios. In [46] a suspension railway crash, which happened in Wuppertal (Germany) in 1999, was studied. In addition, in the authors also analyzed another disaster happened because of a fire in an amusement park in Cologne (Germany) in 2001.…”

Section: Disaster Area Mobility Modelmentioning

confidence: 99%

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Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios

et al. 2013

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decentralized communications quickly and using common devices like mobile phones. Broadcasting is the main mechanism used to disseminate information in all-to-all fashion in ad hoc networks. The objective of this paper is to optimize a broadcasting scheme based on similarity/dissimilarity coefficient designed for disaster response scenarios through a multi-objective optimization problem in which several performance metrics such as reachability, number of retransmissions and delay are optimized simultaneously.

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“…The authors in [78] studied the two different real-life disasters th a t happened in Germany, and divided the disaster area and its surrounding into five different zones: the technical operation command, th e incident site, the casualties treat m ent area, the transport zone, and th e hospital zone. Here, the m obility of the nodes such as medical team s, fire brigades, rescue team s is guided mostly by the regions and the group leader.…”

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confidence: 99%

A study of the Destination Guided Mobility models.

Rahman¹

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Human mobility in MANET disaster area simulation - a realistic approach

Cited by 50 publications

References 6 publications

Realistic mobility simulation of urban mesh networks

Realistic mobility simulation of urban mesh networks

Multi-objective performance optimization of a probabilistic similarity/dissimilarity-based broadcasting scheme for mobile ad hoc networks in disaster response scenarios

A study of the Destination Guided Mobility models.

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