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A statistical analysis of the long-run node spatial distribution in mobile ad hoc networks
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Source International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems archive
Proceedings of the 5th ACM international workshop on Modeling analysis and simulation of wireless and mobile systems table of contents
Atlanta, Georgia, USA
SESSION: Analysis of Ad Hoc Networks table of contents
Pages: 30 - 37  
Year of Publication: 2002
ISBN:1-58113-610-2
Authors
Douglas M. Blough  Georgia Inst. of Technology, Atlanta GA
Giovanni Resta  Istituto di Informatica e Telematica, Area della Ricerca del CNR, Pisa, ITALY
Paolo Santi  Istituto di Informatica e Telematica, Area della Ricerca del CNR, Pisa, ITALY
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we analyze the node spatial distribution of mobile wireless ad hoc networks. Characterizing this distribution is of fundamental importance in the analysis of many relevant properties of mobile ad hoc networks, such as connectivity, average route length, and network capacity. In particular, we have investigated under what conditions the node spatial distribution resulting after a large number of mobility steps resembles the uniform distribution. This is motivated by the fact that the existing theoretical results concerning mobile ad hoc networks are based on this as sumption. In order to test this hypothesis, we performed extensive simulations using two well-known mobility models: the random waypoint model, which resembles intentional movement, and a Brownian-like model, which resembles non-intentional movement. Our analysis has shown that in the Brownian-like motion the uniformity assumption does hold,and that the intensity of the concentration of nodes in the center of the deployment region that occurs in the ran dom waypoint model heavily depends on the choice of some mobility parameters. For extreme values of these parameters,the uniformity assumption is impaired.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  13

Collaborative Colleagues:
Douglas M. Blough: colleagues
Giovanni Resta: colleagues
Paolo Santi: colleagues