American Institute of Mathematical Sciences

Advanced
2012, 2(2): 357-375. doi: 10.3934/naco.2012.2.357

Performance analysis of transmission rate control algorithm from readers to a middleware in intelligent transportation systems

Sangkyu Baek 1, , Jinsoo Park 2, and  Bong Dae Choi 3,

1. 

School of Electrical Engineering, Korea University, 74 Inchon-ro, Seongbuk-gu, Seoul, South Korea
2. 

Central R&D Laboratory, Korea Telecom, 151 Taebong-ro, Seocho-gu, Seoul, South Korea
3. 

Department of Mathematics, Sungkyunkwan University, Seobu-ro, Jangan-gu, Suwon 440-746, South Korea

Received  September 2011 Revised  May 2012 Published  May 2012

Radio Frequency Identification (RFID) systems consisting of tags, readers and a middleware are known as one of the promising technologies to be applied to diverse fields for realizing a ubiquitous society. A typical RFID system where RFID readers collect information from tags on vehicles and send the collected data to a middleware has been used primarily for various distribution and logistics applications. The collected information by the middleware is used for many intelligent transportation systems (ITS) applications such as traffic estimation and real-time navigation. We propose a dynamic transmission rate control algorithm between readers and a middleware with limited buffer capacity environment and present analytical performances. We construct 3-dimensional continuous time Markov chains whose Q-matrix has the form of a quasi-birth and death structure. From the analytical model, we obtain performance measures such as packet loss probability and system throughput. We find the maximum number of readers associated with a middleware while satisfying a constraint on packet loss probability.
Keywords: RFID system, Markov chain, readers, middleware, QBD process..
Mathematics Subject Classification: Primary: 68M20; Secondary: 90B18, 90B2.
Citation: Sangkyu Baek, Jinsoo Park, Bong Dae Choi. Performance analysis of transmission rate control algorithm from readers to a middleware in intelligent transportation systems. Numerical Algebra, Control & Optimization, 2012, 2 (2) : 357-375. doi: 10.3934/naco.2012.2.357
References:
[1]

K. Ali and H. Hassanein, Passive RFID for intelligent transportation systems, in Proc. 6th IEEE Consumer Communications and Networking Conference (CCNC2009), 2009. Google Scholar

[2]

S. Baek, Y. Lim, S. Rhee and K. Choi, Method for estimating population OD matrix based on probe vehicles, KSCE Journal of Civil Engineering, 14 (2010), 231-235. doi: 10.1007/s12205-010-0231-4.  Google Scholar

[3]

M. Bhuotani and S. Moradpour, "RFID Field Guide: Deploying Radio Frequency Identification Systems," Prentice Hall, 2005. Google Scholar

[4]

M. A. Chowdhurry and A. Sadek, "Fundamentals of Intelligent Transportation Systems Planning," Artech House, 2003. Google Scholar

[5]

J. C. Q. Dias, J. M. F. Calado, A. L. Osório and L. F. Morgado, Intelligent transportation system based on RFID and multi-agent approaches, Pervasive Collaborative Networks, 283 (2008), 533-540. doi: 10.1007/978-0-387-84837-2_55.  Google Scholar

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EPCglobal, "The EPCglobal Architecture Framework,", 2007. Available from: \url{http://www.epcglobalinc.org/standards/architecture/architecture_1_2-framework-20070910.pdf}., ().   Google Scholar

[7]

M. Kim, J. Park, J. Oh, H. Chong and Y. Kim, Study on network architecture for traffic inormation collection systems based on RFID technology, in Proc. 2008 IEEE Asia-Pacific Services Computing Conference, 2008. doi: 10.1109/APSCC.2008.170.  Google Scholar

[8]

G. Latoche and V. Ramaswami, "Introduction to Matrix Analytic Methods in Stochastic Modeling," ASA and SIAM, 1999.  Google Scholar

[9]

S. Moon and B. Yang, Effective monitoring of the concrete pouring operation in an RFID-based environment, Journal of Computing in Civil Engineering, 24 (2010), 108-116. doi: 10.1061/(ASCE)CP.1943-5487.0000004.  Google Scholar

[10]

C. Oberli, M. Torres-Territ and D. Landau, Performance evaluation of UHF RFID technologies for real-time passenger recognition in intelligent public transportation systems, IEEE Transactions on Intelligent Transportation Systems, 11 (2010), 748-753. doi: 10.1109/TITS.2010.2048429.  Google Scholar

show all references

References:
[1]

K. Ali and H. Hassanein, Passive RFID for intelligent transportation systems, in Proc. 6th IEEE Consumer Communications and Networking Conference (CCNC2009), 2009. Google Scholar

[2]

S. Baek, Y. Lim, S. Rhee and K. Choi, Method for estimating population OD matrix based on probe vehicles, KSCE Journal of Civil Engineering, 14 (2010), 231-235. doi: 10.1007/s12205-010-0231-4.  Google Scholar

[3]

M. Bhuotani and S. Moradpour, "RFID Field Guide: Deploying Radio Frequency Identification Systems," Prentice Hall, 2005. Google Scholar

[4]

M. A. Chowdhurry and A. Sadek, "Fundamentals of Intelligent Transportation Systems Planning," Artech House, 2003. Google Scholar

[5]

J. C. Q. Dias, J. M. F. Calado, A. L. Osório and L. F. Morgado, Intelligent transportation system based on RFID and multi-agent approaches, Pervasive Collaborative Networks, 283 (2008), 533-540. doi: 10.1007/978-0-387-84837-2_55.  Google Scholar

[6]

EPCglobal, "The EPCglobal Architecture Framework,", 2007. Available from: \url{http://www.epcglobalinc.org/standards/architecture/architecture_1_2-framework-20070910.pdf}., ().   Google Scholar

[7]

M. Kim, J. Park, J. Oh, H. Chong and Y. Kim, Study on network architecture for traffic inormation collection systems based on RFID technology, in Proc. 2008 IEEE Asia-Pacific Services Computing Conference, 2008. doi: 10.1109/APSCC.2008.170.  Google Scholar

[8]

G. Latoche and V. Ramaswami, "Introduction to Matrix Analytic Methods in Stochastic Modeling," ASA and SIAM, 1999.  Google Scholar

[9]

S. Moon and B. Yang, Effective monitoring of the concrete pouring operation in an RFID-based environment, Journal of Computing in Civil Engineering, 24 (2010), 108-116. doi: 10.1061/(ASCE)CP.1943-5487.0000004.  Google Scholar

[10]

C. Oberli, M. Torres-Territ and D. Landau, Performance evaluation of UHF RFID technologies for real-time passenger recognition in intelligent public transportation systems, IEEE Transactions on Intelligent Transportation Systems, 11 (2010), 748-753. doi: 10.1109/TITS.2010.2048429.  Google Scholar

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