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Journal articles on the topic 'Traffic engineering'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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1

Otoshi, Tatsuya, Yuichi Ohsita, Masayuki Murata, Yousuke Takahashi, Keisuke Ishibashi, and Kohei Shiomoto. "Traffic prediction for dynamic traffic engineering." Computer Networks 85 (July 2015): 36–50. http://dx.doi.org/10.1016/j.comnet.2015.05.001.

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2

Marbukh, Vladimir. "Robust traffic engineering." ACM SIGMETRICS Performance Evaluation Review 30, no. 3 (December 2002): 17–19. http://dx.doi.org/10.1145/605521.605529.

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3

Hendling, K., G. Franzl, and K. Bengi. "Internet traffic engineering." e & i Elektrotechnik und Informationstechnik 121, no. 6 (June 2004): 239–42. http://dx.doi.org/10.1007/bf03055356.

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4

Roughan, Matthew, Mikkel Thorup, and Yin Zhang. "Performance of estimated traffic matrices in traffic engineering." ACM SIGMETRICS Performance Evaluation Review 31, no. 1 (June 10, 2003): 326–27. http://dx.doi.org/10.1145/885651.781080.

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5

Zhang, Dengyin, Zhiyun Tang, and Ruchuan Wang. "Automatic Traffic Balance Algorithm Based on Traffic Engineering." Journal of Network and Systems Management 14, no. 3 (July 22, 2006): 317–25. http://dx.doi.org/10.1007/s10922-006-9034-9.

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6

Uhlig, Steve, and Olivier Bonaventure. "Implications of Interdomain Traffic Characteristics on Traffic Engineering." European Transactions on Telecommunications 13, no. 1 (January 2002): 23–32. http://dx.doi.org/10.1002/ett.4460130104.

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7

Retvari, G., and T. Cinkler. "Practical OSPF Traffic Engineering." IEEE Communications Letters 8, no. 11 (November 2004): 689–91. http://dx.doi.org/10.1109/lcomm.2004.837629.

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8

Frank, Benjamin, Ingmar Poese, Georgios Smaragdakis, Steve Uhlig, and Anja Feldmann. "Content-aware traffic engineering." ACM SIGMETRICS Performance Evaluation Review 40, no. 1 (June 7, 2012): 413–14. http://dx.doi.org/10.1145/2318857.2254819.

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9

Dasgupta, Sukrit, Jaudelice C. de Oliveira, and J. P. Vasseur. "Dynamic traffic engineering for mixed traffic on international networks." Computer Networks 52, no. 11 (August 2008): 2237–58. http://dx.doi.org/10.1016/j.comnet.2008.04.005.

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10

Singh, Amarpreet, Sandeep Singh, and Alok Aggarwal. "ADAPTIVE TRAFFIC SYSTEM CONTROLLERS IN TRAFFIC ENGINEERING : A SURVEY." Suranaree Journal of Science and Technology 30, no. 3 (December 15, 2023): 010224. http://dx.doi.org/10.55766/sujst-2023-03-e03030.

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In today’s era, traffic congestion is the widest spread problem observed all over the world, arising as consequence of exponential rise in vehicle count at the traffic intersections. This growth has largely affected the people as they are experiencing enhanced delay in travelling time and increased fuel consumption which led to wastage of billions of dollars. The current road infrastructure design and traffic signal controlling using a cycle of fixed time phase of green/red/yellow lights are not adequate to tackle the rising demands of traffic in an optimum way. These traditional traffic signal systems cannot handle the dynamics of road traffic at the intersections and hence results in exceeding delays. Also, the volume of traffic at any intersection at different times of the day is uncertain and hence it is hard to get an exact mathematical model for this problem. Many researchers have proposed some solution to this problem and their work is reviewed extensively in this paper. Due to its ability to deal with uncertainty, fuzzy logic is considered as the most appropriate technique to solve this problem and is highly recommended method for implementing automated traffic controllers. Due to its inherent advantages, most of the research in the field of traffic engineering is carried out using fuzzy logic techniques. Hence, this paper presents a systematic review of various techniques that are used for an effective management of traffic, especially focusing on different fuzzy based traffic controllers and their performance comparison to identify the best input output parameter.

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11

Hussein, Hatim S. "Multipath Bandwidth Capacity Allocation and MPLS Internet Traffic Engineering." Journal of Advances in Computer Networks 3, no. 3 (2015): 239–42. http://dx.doi.org/10.7763/jacn.2015.v3.174.

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12

Abbasi, Mohammad Reza, Ajay Guleria, and Mandalika S. Devi. "Traffic Engineering in Software Defined Networks: A Survey." Journal of Telecommunications and Information Technology, no. 4 (December 30, 2016): 3–14. http://dx.doi.org/10.26636/jtit.2016.4.757.

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An important technique to optimize a network and improve network robustness is traffic engineering. As traffic demand increases, traffic engineering can reduce service degradation and failure in the network. To allow a network to adapt to changes in the traffic pattern, the research community proposed several traffic engineering techniques for the traditional networking architecture. However, the traditional network architecture is difficult to manage. Software Defined Networking (SDN) is a new networking model, which decouples the control plane and data plane of the networking devices. It promises to simplify network management, introduces network programmability, and provides a global view of network state. To exploit the potential of SDN, new traffic engineering methods are required. This paper surveys the state of the art in traffic engineering techniques with an emphasis on traffic engineering for SDN. It focuses on some of the traffic engineering methods for the traditional network architecture and the lessons that can be learned from them for better traffic engineering methods for SDN-based networks. This paper also explores the research challenges and future directions for SDN traffic engineering solutions.

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13

Otoshi, Tatsuya, Yuichi Ohsita, Masayuki Murata, Yousuke Takahashi, Keisuke Ishibashi, Kohei Shiomoto, and Tomoaki Hashimoto. "Hierarchical Model Predictive Traffic Engineering." IEEE/ACM Transactions on Networking 26, no. 4 (August 2018): 1754–67. http://dx.doi.org/10.1109/tnet.2018.2850377.

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14

Zheng Wang. "Internet traffic engineering [Guest Editorial]." IEEE Network 14, no. 2 (March 2000): 10. http://dx.doi.org/10.1109/mnet.2000.826366.

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15

Ali, M., G. Chiruvolu, An Ge, and Alcatel. "Traffic engineering in metro ethernet." IEEE Network 19, no. 2 (March 2005): 10–17. http://dx.doi.org/10.1109/mnet.2005.1407693.

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16

Skabardonis, Alexander. "Microcomputer Applications in Traffic Engineering." Journal of Transportation Engineering 112, no. 1 (January 1986): 1–14. http://dx.doi.org/10.1061/(asce)0733-947x(1986)112:1(1).

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17

Zarrillo, Marguerite L. "Traffic Engineering Handbook (Fifth Edition)." Journal of Transportation Engineering 127, no. 2 (April 2001): 178–79. http://dx.doi.org/10.1061/(asce)0733-947x(2001)127:2(178.2).

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18

Truong Dinh, Khoa, Sławomir Kukliński, Tomasz Osiński, and Jacek Wytrębowicz. "Heuristic traffic engineering for SDN." Journal of Information and Telecommunication 4, no. 3 (June 4, 2020): 251–66. http://dx.doi.org/10.1080/24751839.2020.1755528.

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19

MacGregor, M. H., W. D. Grover, and U. M. Maydell. "The self-traffic-engineering network." Canadian Journal of Electrical and Computer Engineering 18, no. 2 (April 1993): 47–58. http://dx.doi.org/10.1109/cjece.1993.6592815.

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20

Hendrickson, Chris, and Larry Rilett. "Traffic Simulation and Transportation Engineering." Journal of Transportation Engineering, Part A: Systems 143, no. 12 (December 2017): 01817002. http://dx.doi.org/10.1061/jtepbs.0000091.

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21

Poese, Ingmar, Benjamin Frank, Georgios Smaragdakis, Steve Uhlig, Anja Feldmann, and Bruce Maggs. "Enabling content-aware traffic engineering." ACM SIGCOMM Computer Communication Review 42, no. 5 (September 24, 2012): 21–28. http://dx.doi.org/10.1145/2378956.2378960.

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22

Elwalid, Anwar, Cheng Jin, Steven Low, and Indra Widjaja. "MATE: multipath adaptive traffic engineering." Computer Networks 40, no. 6 (December 2002): 695–709. http://dx.doi.org/10.1016/s1389-1286(02)00308-0.

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23

Swallow, G. "MPLS advantages for traffic engineering." IEEE Communications Magazine 37, no. 12 (1999): 54–57. http://dx.doi.org/10.1109/35.809385.

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24

Feamster, Nick, Jay Borkenhagen, and Jennifer Rexford. "Guidelines for interdomain traffic engineering." ACM SIGCOMM Computer Communication Review 33, no. 5 (October 2003): 19–30. http://dx.doi.org/10.1145/963985.963988.

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25

Mortier, R. M. "Multi-timescale Internet traffic engineering." IEEE Communications Magazine 40, no. 10 (October 2002): 125–31. http://dx.doi.org/10.1109/mcom.2002.1039867.

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26

Quoitin, B., C. Pelsser, L. Swinnen, O. Bonaventure, and S. Uhlig. "Interdomain traffic engineering with BGP." IEEE Communications Magazine 41, no. 5 (May 2003): 122–28. http://dx.doi.org/10.1109/mcom.2003.1200112.

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27

Wolch, Thomas E. "The State of Traffic Engineering." Journal of Professional Issues in Engineering Education and Practice 137, no. 4 (October 2011): 208–10. http://dx.doi.org/10.1061/(asce)ei.1943-5541.0000062.

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28

Guo, Yingya, Zhiliang Wang, Xia Yin, Xingang Shi, and Jianping Wu. "Traffic engineering in hybrid SDN networks with multiple traffic matrices." Computer Networks 126 (October 2017): 187–99. http://dx.doi.org/10.1016/j.comnet.2017.07.008.

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29

Yu, Yi Fan, Yong Li, and De Peng Jin. "Dynamical Traffic Engineering in Software-Defined Network." Applied Mechanics and Materials 610 (August 2014): 954–58. http://dx.doi.org/10.4028/www.scientific.net/amm.610.954.

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Software-Defined Networks (SDN), as newly proposed network architecture, has a great potential in optimizing network traffics. In SDN, the control plane is separated from the data plane. With the help of the centralized controller, we can gather information of the network in real time. In this work, we propose a practical two-stage approach for traffic engineering that takes advantages of SDN. The approach not only assures every newly injected flow gets a suitable route that does not have too much payload on it, but also schedules the overall flows so that they are distributed more equally in the network. Furthermore, we demonstrate its efficiency in terms of port speed and compared it with port speed under the default routing decision. We also use linear programming to find the optimal solution and compare it with our result.

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30

Amrizal, Amrizal, Pagit Juni S Br Tarigan, and Egi Pramono. "Traffic Engineering At The Kim Ii Roundabout." International Journal of Science, Technology & Management 5, no. 2 (March 27, 2024): 358–66. http://dx.doi.org/10.46729/ijstm.v5i2.981.

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As the manager of the industrial area, currently PT. KIM has problems related to traffic jams that occur around the KIM roundabout and to reduce the number of traffic accidents at KIM due to collisions between vehicles from opposite directions, it is necessary to carry out traffic engineering in the area. Traffic engineering is related to the implementation of repair work Roundabouts are not only road construction improvements but also include traffic engineering before, during and after construction. Simulation of traffic conditions to provide alternative solutions to traffic problems that occur at the KIM II Roundabout using VISSIM software. From the results of the simulations that have been carried out, it can be seen that almost all road sections have a level of service F, which means they have a VCR value > 1. This is included in the oversaturated category, side obstacles and delays increase, stopping and moving events increase, if the flow increases, the vehicle speed is equal to zero (complete stop). This condition causes delays on one of the sections of 151 vehicle seconds and this condition is not very good because it will lengthen the queue of vehicles crossing the roundabout. In accordance with the simulation that has been carried out, and based on several applicable regulations regarding the traffic system at roundabouts, several alternatives for handling traffic problems in the KIM II Roundabout area are provided.

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31

SATAKE, Kodai, Tatsuya OTOSHI, Yuichi OHSITA, and Masayuki MURATA. "Traffic Engineering and Traffic Monitoring in the Case of Incomplete Information." IEICE Transactions on Communications E102.B, no. 1 (January 1, 2019): 111–21. http://dx.doi.org/10.1587/transcom.2018ebp3049.

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32

Guo, Qi, Dan Li, and Qing Fang. "Study on the Environmental Impact Assessment Index of Traffic Engineering Based on the Low Carbon Economy Perspective." Advanced Materials Research 599 (November 2012): 206–10. http://dx.doi.org/10.4028/www.scientific.net/amr.599.206.

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The traffic engineering environment impact assessment generally considered the influence on environment of traffic engineering operation stage only, relatively ignored the influence on environment of traffic engineering construction stage and demolition stage. This paper gives comprehensive analysis on the influence on environment of traffic engineering at the view of the whole life cycle of traffic engineering. That is considering the influence on environment of materiel production stage, processing stage, engineering construction stage and demolition stage. The traffic engineering environment impact assessment index is established by considering a low carbon economy connotation and with the use of total life cycle analysis method, and the evaluation index of each specific quantitative index is given.

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33

K Aneja, Kawalpreet. "Traffic Light Reporter for Genome Engineering." Acta Scientific Microbiology 3, no. 9 (August 18, 2020): 27–28. http://dx.doi.org/10.31080/asmi.2020.03.0672.

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34

KAMIYAMA, Noriaki, Yousuke TAKAHASHI, Keisuke ISHIBASHI, Kohei SHIOMOTO, Tatsuya OTOSHI, Yuichi OHSITA, and Masayuki MURATA. "Effective Flow Aggregation for Traffic Engineering." IEICE Transactions on Communications E98.B, no. 10 (2015): 2049–59. http://dx.doi.org/10.1587/transcom.e98.b.2049.

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35

Khan, Mohsin. "MPLS Traffic Engineering in ISP Network." International Journal of Computer Applications 59, no. 4 (December 18, 2012): 23–32. http://dx.doi.org/10.5120/9536-3972.

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36

Pande, Anurag, and Joe Grimes. "Traffic Engineering in a Hybrid Format." Transportation Research Record: Journal of the Transportation Research Board 2211, no. 1 (January 2011): 18–26. http://dx.doi.org/10.3141/2211-03.

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37

Pereira, Vitor, Miguel Rocha, and Pedro Sousa. "Traffic Engineering With Three-Segments Routing." IEEE Transactions on Network and Service Management 17, no. 3 (September 2020): 1896–909. http://dx.doi.org/10.1109/tnsm.2020.2993207.

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38

Liu, Hongqiang Harry, Srikanth Kandula, Ratul Mahajan, Ming Zhang, and David Gelernter. "Traffic engineering with forward fault correction." ACM SIGCOMM Computer Communication Review 44, no. 4 (February 25, 2015): 527–38. http://dx.doi.org/10.1145/2740070.2626314.

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39

Feldmann, A., A. Greenberg, C. Lund, N. Reingold, and J. Rexford. "NetScope: traffic engineering for IP networks." IEEE Network 14, no. 2 (2000): 11–19. http://dx.doi.org/10.1109/65.826367.

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40

Sharma, Abhigyan, Arun Venkataramani, and Ramesh K. Sitaraman. "Distributing content simplifies ISP traffic engineering." ACM SIGMETRICS Performance Evaluation Review 41, no. 1 (June 14, 2013): 229–42. http://dx.doi.org/10.1145/2494232.2465764.

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41

Suri, Subhash, Marcel Waldvogel, Daniel Bauer, and Priyank Ramesh Warkhede. "Profile-based routing and traffic engineering." Computer Communications 26, no. 4 (March 2003): 351–65. http://dx.doi.org/10.1016/s0140-3664(02)00154-8.

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42

Roughan, Matthew, and Yin Zhang. "GATEway: symbiotic inter-domain traffic engineering." Telecommunication Systems 47, no. 1-2 (May 5, 2010): 3–17. http://dx.doi.org/10.1007/s11235-010-9298-y.

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43

Tizghadam, Ali, and Alberto Leon-Garcia. "Autonomic traffic engineering for network robustness." IEEE Journal on Selected Areas in Communications 28, no. 1 (January 2010): 39–50. http://dx.doi.org/10.1109/jsac.2010.100105.

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44

Quoitin, B., S. Tandel, S. Uhlig, and O. Bonaventure. "Interdomain traffic engineering with redistribution communities." Computer Communications 27, no. 4 (March 2004): 355–63. http://dx.doi.org/10.1016/j.comcom.2003.08.008.

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45

Leduc, G., H. Abrahamsson, S. Balon, S. Bessler, M. D'Arienzo, O. Delcourt, J. Domingo-Pascual, et al. "An open source traffic engineering toolbox." Computer Communications 29, no. 5 (March 2006): 593–610. http://dx.doi.org/10.1016/j.comcom.2005.06.010.

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46

Moreno, Eduardo, Alejandra Beghelli, and Filippo Cugini. "Traffic engineering in segment routing networks." Computer Networks 114 (February 2017): 23–31. http://dx.doi.org/10.1016/j.comnet.2017.01.006.

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47

Le Gall, Pierre. "Packetized traffic engineering for new services." Computer Networks and ISDN Systems 20, no. 1-5 (December 1990): 425–33. http://dx.doi.org/10.1016/0169-7552(90)90053-u.

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48

Puype, Bart, Didier Colle, Mario Pickavet, and Piet Demeester. "Multilayer traffic engineering for multiservice environments." Photonic Network Communications 18, no. 2 (October 9, 2008): 150–59. http://dx.doi.org/10.1007/s11107-008-0179-1.

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49

Puype, Bart, Willem Vereecken, Didier Colle, Mario Pickavet, and Piet Demeester. "Multilayer traffic engineering for energy efficiency." Photonic Network Communications 21, no. 2 (September 10, 2010): 127–40. http://dx.doi.org/10.1007/s11107-010-0287-6.

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50

Audat, Ahmad, Marah Yahia, Said Ghoul, and Maram Bani Younes. "Traffic Light Control Systems: Requirements Engineering." International Journal of Network Security & Its Applications 16, no. 1 (January 29, 2024): 01–20. http://dx.doi.org/10.5121/ijnsa.2024.16101.

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Requirements Engineering (RE) is the most important activity and pivot phase in the software development life cycle. It consists mainly of requirements analysis, design, and specification. The application of RE in a business domain aims to generalize its different specific approaches by meta-models under which each specific approach is an instance or specialization. RE is being applied more and more in different business domains, and its application benefits are found to be valuable. Despite these active RE applications and their added values in different domains, the Traffic Light Control (TLC) domain has not yet been approached, regardless of its everyday interest. The work presented in this paper is part of a TLC enhancement project that explores RE's potential contributions to leveraging TLC quality. Thus, in this work, different recent specific approaches to TLC are analyzed, and a large part of this business domain's functional/ non-functional requirements are elicited and specified. Moreover, the traffic context-aware traffic light control systems (CTLC) are also considered. They are deeply analyzed and compared to the typical TLC systems. As a primary result, the tangling of different concerns was stated, and a separate concerns paradigm was applied. This leads to requirements specification through separated agents. This should lead to TLC and CTLC systems development and maintenance cost reduction. An important agent dealing with security aspects and their evolving technologies is introduced. The impact evaluations of the RE on some TLC and CTLC current approaches are also presented.

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