Dynamic Performance Analysis of Uplink Transmission in Cluster-Based Heterogeneous Vehicular Networks
As an emerging technology, vehicular networks have evolved into an indispensable part of intelligent transport systems (ITS). Thus, this paper focuses on the performance analysis of the cluster-based heterogeneous vehicular networks (C-HetVNETs) with dynamic data arrival rate and different vehicle d...
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Published in | IEEE transactions on vehicular technology Vol. 64; no. 12; pp. 5584 - 5595 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.12.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
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Abstract | As an emerging technology, vehicular networks have evolved into an indispensable part of intelligent transport systems (ITS). Thus, this paper focuses on the performance analysis of the cluster-based heterogeneous vehicular networks (C-HetVNETs) with dynamic data arrival rate and different vehicle densities. Different from the previous studies, which mainly focus on network capacity in just one wireless-technology-supported vehicular network, such as dedicated short-range communication (DSRC) or Third-Generation Partnership Project (3GPP) long-term evolution (LTE), we focus on the different performance metrics of uplink transmission in C-HetVNET. First, we develop a framework of C-HetVNET by employing the cluster mechanism. Then, the performance analysis models of intracluster and intercluster communications are designed based on a Markov queuing model. Due to the explosion of state space, model decomposition and iteration techniques are proposed to handle this problem. Based on the developed analytical model, the performance metrics of different scheduling schemes, in terms of throughput, delay, dropping probability, and queue length, are studied and compared. The performances of C-HetVNETs under different vehicle densities and data arrival rates are obtained via analysis and simulations, which give a useful guideline for network configuration of C-HetVNETs. The proposed analytical model can be also used for heterogeneous or two-tier network analysis and validation of network simulators under various traffic conditions. In addition, we investigate the performances of LTE networks used for vehicular communications for the purpose of performance comparison. |
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AbstractList | As an emerging technology, vehicular networks have evolved into an indispensable part of intelligent transport systems (ITS). Thus, this paper focuses on the performance analysis of the cluster-based heterogeneous vehicular networks (C-HetVNETs) with dynamic data arrival rate and different vehicle densities. Different from the previous studies, which mainly focus on network capacity in just one wireless-technology-supported vehicular network, such as dedicated short-range communication (DSRC) or Third-Generation Partnership Project (3GPP) long-term evolution (LTE), we focus on the different performance metrics of uplink transmission in C-HetVNET. First, we develop a framework of C-HetVNET by employing the cluster mechanism. Then, the performance analysis models of intracluster and intercluster communications are designed based on a Markov queuing model. Due to the explosion of state space, model decomposition and iteration techniques are proposed to handle this problem. Based on the developed analytical model, the performance metrics of different scheduling schemes, in terms of throughput, delay, dropping probability, and queue length, are studied and compared. The performances of C-HetVNETs under different vehicle densities and data arrival rates are obtained via analysis and simulations, which give a useful guideline for network configuration of C-HetVNETs. The proposed analytical model can be also used for heterogeneous or two-tier network analysis and validation of network simulators under various traffic conditions. In addition, we investigate the performances of LTE networks used for vehicular communications for the purpose of performance comparison. |
Author | Liang Sun Leung, Victor C. M. Kan Zheng Qiang Zheng |
Author_xml | – sequence: 1 surname: Qiang Zheng fullname: Qiang Zheng organization: Wireless Signal Process. & Network Lab., Beijing Univ. of Postsand Telecommun., Beijing, China – sequence: 2 surname: Kan Zheng fullname: Kan Zheng email: kzheng@ieee.org organization: Wireless Signal Process. & Network Lab., Beijing Univ. of Postsand Telecommun., Beijing, China – sequence: 3 surname: Liang Sun fullname: Liang Sun organization: Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada – sequence: 4 givenname: Victor C. M. surname: Leung fullname: Leung, Victor C. M. organization: Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada |
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Cites_doi | 10.1109/MCOM.2015.7060498 10.1109/MWC.2011.5714026 10.1109/JSAC.2014.141202 10.1109/JPROC.2011.2132790 10.1109/JSAC.2011.110306 10.1109/TITS.2013.2253554 10.1109/TVT.2007.907233 10.1109/TVT.2010.2044905 10.1109/TITS.2012.2213595 10.1109/WCL.2012.022012.120073 10.1109/TWC.2009.080523 10.1109/TITS.2013.2258153 10.1109/ICC.2012.6364412 10.1109/COMST.2015.2440103 10.1109/TWC.2012.122212.120223 10.1109/PNPM.1995.524312 10.1109/JSAC.2011.110107 10.1109/JSAC.2011.110108 10.1109/JSTSP.2014.2330343 10.1109/TWC.2013.101613.122076 10.1109/MCOM.2014.6829960 10.1109/TVT.2008.929219 10.1016/S1007-0214(09)70049-5 10.1109/MITS.2010.938166 10.1109/TITS.2013.2293472 10.1109/MCOM.2013.6515060 10.1109/TVT.2013.2244929 10.1109/TVT.2014.2323693 10.1109/CCNC.2012.6181109 10.1109/IWCMC.2013.6583804 10.1109/TCOMM.2014.2328574 10.1109/TITS.2012.2183366 10.1109/TCOMM.2015.2388575 10.1109/JSAC.2011.110307 10.1109/GIIS.2011.6026706 |
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Keywords | Dedicated short-range communication (DSRC) long-term evolution (LTE) vehicle to infrastructure (V2I) vehicle to vehicle (V2V) heterogeneous vehicular networks (HetVNETs) performance analysis |
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SubjectTerms | Analytical models Business metrics Connected vehicles Dedicated Short Range Communication (DSRC) Density Heterogeneous vehicular networks (HetVNETs) Long Term Evolution Long Term Evolution (LTE) Markov analysis Mathematical analysis Mobile communication systems Networks Performance analysis Performance measurement Queuing theory Transmissions (automotive) Uplink Uplinking Vehicle-to- Infrastructure (V2I) Vehicle-to-Vehicle (V2V) Vehicular ad hoc networks Wireless communication |
Title | Dynamic Performance Analysis of Uplink Transmission in Cluster-Based Heterogeneous Vehicular Networks |
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