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Wireless Networks
Erschienen in: Wireless Networks 6/2016

01.08.2016

Vehicle mobility driven by traditional drivers versus connected drivers

verfasst von: Lin Li, Yanheng Liu, Jian Wang, Weiwen Deng, Heekuck Oh

Erschienen in: Wireless Networks | Ausgabe 6/2016

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Abstract

The traditional vehicle mobility is restricted to the driver habits and the line-of-sight. The new-emerging connected vehicles enable information exchange with each other at vicinity, which will undoubtedly bring a greatly positive effect on the vehicle mobility pattern. In this paper, we propose to modeling and analyzing the vehicle mobility patterns respectively driven by traditional drivers and connected drivers. We perform the extensive simulations to explore the statistical differences between two mobility patterns and the underlying reasons through comparing to the real vehicle trace datasets. The results show that they behave quite diversely at the concerned aspects, e.g. degree distribution, clustering coefficient, topological shortest path, topological coefficient, and vehicle density, and also we find that the connected vehicles are well distributed and contribute a relieved traffic congestion situation.
Vorheriger Artikel On MAC optimization for large-scale wireless sensor network
Nächster Artikel A grid based clustering and routing algorithm for solving hot spot problem in wireless sensor networks

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Literatur
1.
2.
Jing, Q., Vasilakos, A. V., Wan, J., et al. (2014). Security of the internet of things: Perspectives and challenges. Wireless Networks, 20(8), 2481–2501.CrossRef
3.
Li, P., Guo, S., Yu, S., et al. (2014). Reliable multicast with pipelined network coding using opportunistic feeding and routing. IEEE Transactions on Parallel and Distributed Systems, 25(12), 3264–3273.CrossRef
4.
Liu, X. Y., Zhu, Y., Kong, L., et al. (2014). CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(8), 2188–2197.CrossRef
5.
Rahimi, M. R., Ren, J., Liu, C. H., et al. (2014). Mobile cloud computing: A survey, state of art and future directions. Mobile Networks and Applications, 19(2), 133–143.CrossRef
6.
Rahimi, M, R., Venkatasubramanian, N., & Vasilakos, A. V. (2013). Music: Mobility-aware optimal service allocation in mobile cloud computing. In 2013 IEEE Sixth International Conference on Cloud Computing, IEEE (pp. 75–82).
7.
Sheng, Z., Yang, S., Yu, Y., et al. (2013). A survey on the ietf protocol suite for the internet of things: Standards, challenges, and opportunities. IEEE Wireless Communications, 20(6), 91–98.CrossRef
8.
Camp, T., Boleng, J., & Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless Communications and Mobile Computing, 2(5), 483–502.CrossRef
9.
Chu, T., & Nikolaidis, I. (2002). On the artifacts of random waypoint simulations. In International Conference on Internet Computing (pp. 69–76).
10.
Yoon, J., Liu, M., & Noble, B. (2003). Sound mobility models. In Proceedings of the 9th annual international conference on Mobile computing and networking. ACM (pp. 205–216).
11.
Zeng, Y., Xiang, K., Li, D., et al. (2013). Directional routing and scheduling for green vehicular delay tolerant networks. Wireless Networks, 19(2), 161–173.CrossRef
12.
Zhou, L., Zhang, Y., Song, K., et al. (2011). Distributed media services in P2P-based vehicular networks. IEEE Transactions on Vehicular Technology, 60(2), 692–703.CrossRef
13.
Fiore, M., & Härri, J. (2008). The networking shape of vehicular mobility. In Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing. ACM (pp. 261–272).
14.
Ait Ali, K., Baala, O., & Caminada, A. (2015). On the spatiotemporal traffic variation in vehicle mobility modeling. IEEE Transactions on Vehicular Technology, 64(2), 652–667.CrossRef
15.
Mahajan, A., et al. (2006). Urban mobility models for VANETs. In 2nd IEEE International Workshop on Next Generation Wireless Networks.
16.
Kumar, D., Dayal, A. K. (2005). Comparative study of mobility models for MANETs & study of vehicular ad-hoc networks. Bachelor of Science thesis, Indian Institute of Technology, New Delhi, India.
17.
Jaap, S., Bechler, M., & Wolf, L. (2005). Evaluation of routing protocols for vehicular ad hoc networks in city traffic scenarios. In International Conference on Intelligent Transportation Systems Telecommunication (ITST), Brest, France.
18.
Viriyasitavat, W., Boban, M., Tsai, H. M., et al. (2015). Vehicular communications: Survey and challenges of channel and propagation models. IEEE Vehicular Technology Magazine, 10(2), 55–66.CrossRef
19.
Cunha, F. D., Carneiro Vianna, A., Mini, R., et al. (2014). Is it possible to find social properties in vehicular networks? In 2014 IEEE Symposium on Computers and Communication, IEEE (pp. 1–6).
20.
Zhang, X. M., Zhang, Y., Yan, F., et al. (2015). Interference-based topology control algorithm for delay-constrained mobile Ad hoc networks. IEEE Transactions on Mobile Computing, 14(4), 742–754.CrossRef
21.
Acampora, G., et al. (2010). Interoperable and adaptive fuzzy services for ambient intelligence applications. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 5(2), 1–26.CrossRef
22.
Yang, M., Li, Y., Jin, D., et al. (2014). Software-defined and virtualized future mobile and wireless networks: A survey. Mobile Networks and Applications, 20(1), 4–18.CrossRef
23.
Jin, L., Chen, Y., Wang, T., et al. (2013). Understanding user behavior in online social networks: A survey. IEEE Communications Magazine, 51(9), 144–150.CrossRef
24.
Dvir, A., & Vasilakos, A. V. (2011). Backpressure-based routing protocol for DTNs. ACM SIGCOMM Computer Communication Review, 41(4), 405–406.
25.
Leskovec, J., Kleinberg, J., & Faloutsos, C. (2007). Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data (TKDD), 1(1), 2.CrossRef
26.
Zhou, L., Naixue, X., Shu, L., et al. (2010). Context-Aware middleware for multimedia services in heterogeneous networks. IEEE Intelligent Systems, 25(2), 40–47.CrossRef
27.
Loulloudes, N., Pallis, G., & Dikaiakos, M. D. (2010). The dynamics of vehicular networks in urban environments. arXiv:​1007.​4106.
28.
Liu, X., Li, Z., Li, W. et al. (2012). Exploring social properties in vehicular ad hoc networks. In Proceedings of the Fourth Asia-Pacific Symposium on Internetware. ACM (pp. 1–24).
29.
Davies, V. A. (2000). Evaluating mobility models within an ad hoc network. advisor: Tracy Camp, Department of Mathematical and Computer Sciences. Colorado School of Mines.
30.
Liu, Z., Liu, Y., Wang, J., & Deng, W. (2015). Modeling and simulating traffic congestion propagation in connected vehicles driven by temporal and spatial preference. Wireless Networks,. doi:10.​1007/​s11276-015-1021-1.
31.
Akhtar, N., Ozkasap, O., & Ergen, S. C. (2013). VANET topology characteristics under realistic mobility and channel models. In IEEE Wireless Communications and Networking Conference (WCNC), IEEE (pp. 1774–1779).
32.
Metadaten
Titel
Vehicle mobility driven by traditional drivers versus connected drivers
verfasst von
Lin Li
Yanheng Liu
Jian Wang
Weiwen Deng
Heekuck Oh
Publikationsdatum
01.08.2016
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 6/2016
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-015-1078-x

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