Modeling the Sociological Characteristic of Vehicle Mobility in Vehicular Sensor Network

Article Preview

Abstract:

Many mobility models have been proposed for the simulation of vehicular sensor network, however, the existing models seldom consider the sociological Aspects of vehicle movement. The paper firstly analyzed the social characteristic of mobility of the real vehicular traces and gained the conclusion that is short average distance, limited node degree and high cluster coefficient. Based on it, a mobility model based social network is proposed and turned into a simulation, which consists of growing and evolvement of social networks, geographical location mapping of vehicles and node dynamics. The simulation results proved that the model’s characteristic is similar to real trace.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

715-718

Citation:

Online since:

February 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Vasco N.G.J. Soares, Farid Farahmand, Joel P.C. Rodrigues. A Layered Architecture for Vehicular Delay-Tolerant Networks. Proc of IEEE Symposium on Computers and Communications (ISCC'09), Sousse, Tunisia, 2009: 122~127.

DOI: 10.1109/iscc.2009.5202332

Google Scholar

[2] Andres Rojas, Philip Branch, Grenville Armitage. Experimental Validation of the Random Waypoint Mobility Model through a Real World Mobility Trace for Large Geographical Areas. Proc of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems, Montreal, Canada, October (2005).

DOI: 10.1145/1089444.1089474

Google Scholar

[3] W. Hsu, K. Merchant, H. Shu, et al. Weighted Waypoint Mobility Model and its Impact on Ad Hoc Networks. Proc of ACM Mobile Computer Communications Review (MC2R), Jan 2005: 59~6.

DOI: 10.1145/1055959.1055968

Google Scholar

[4] Mirco Musolesi, Cecilia Mascolo. A Community Based Mobility Model for Ad Hoc Network Research. Proc of the 2nd ACM/SIGMOBILE International Workshop on Multi-hop Ad Hoc Networks: from theory to reality (REALMAN'06), Florence, Italy, May (2006).

DOI: 10.1145/1132983.1132990

Google Scholar

[5] Jerome Harri, Fethi Filali and Christian Bonnet. Mobility Models for Vehicular Ad Hoc Networks: A Survey and Taxonomy. EURECOM Research Report RR-06-168 2006-5.

DOI: 10.1109/surv.2009.090403

Google Scholar

[6] A. Chaintreau, P. Hui, J. Crowcroft, C. Diot, R. Gass, and J. Scott. Pocket Switched Networks: Real-world mobility and its consequences for opportunistic forwarding. Technical Report UCAM-CL-TR-617, University of Cambridge, Computer Laboratory, February (2005).

DOI: 10.1145/1080139.1080142

Google Scholar

[7] K. Hermann. Modeling the sociological aspect of mobility in ad hoc networks. In Proceedings of MSWiM'03, pages 128–129, San Diego, California, USA, September (2003).

Google Scholar

[8] M. Musolesi and C. Mascolo. A Community Based Mobility Model for Ad Hoc Network Research. In Proceedings of the Second International Workshop on Multi-hop Ad Hoc Networks (REALMAN), May (2006).

DOI: 10.1145/1132983.1132990

Google Scholar

[9] C. Boldrini, M. Conti, and A. Passarella. Users mobility models for opportunistic networks: the role of physical locations. In Proc. of IEEE WRECOM, (2007).

Google Scholar

[10] W. -J. Hsu, T. Spyropoulos, K. Psounis, and A. Helmy, Modeling time-variant user mobility in wireless mobile networks, in Proceedings IEEE INFOCOM, (2007).

DOI: 10.1109/infcom.2007.94

Google Scholar

[11] X. Wu and Z. Liu, Physica A, 387(2008)623.

Google Scholar