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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
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  3/2021 - 4

 HIGH-IMPACT PAPER 

Performance Analysis of Ryu-POX Controller in Different Tree-Based SDN Topologies

CABARKAPA, D. See more information about CABARKAPA, D. on SCOPUS See more information about CABARKAPA, D. on IEEExplore See more information about CABARKAPA, D. on Web of Science, RANCIC, D. See more information about RANCIC, D. on SCOPUS See more information about RANCIC, D. on SCOPUS See more information about RANCIC, D. on Web of Science
 
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Download PDF pdficon (1,704 KB) | Citation | Downloads: 2,127 | Views: 2,505

Author keywords
network topology, next generation networking, tree data structures, software defined networking, soft switching

References keywords
openflow(10), performance(9), networks(8), software(7), controller(7), networking(6), defined(6), controllers(6), network(5), link(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-08-31
Volume 21, Issue 3, Year 2021, On page(s): 31 - 38
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.03004
Web of Science Accession Number: 000691632000004
SCOPUS ID: 85121586882

Abstract
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Next generation networking architecture is required to be reliable, scalable, flexible, secure and has other advanced features. Traditional TCPIP networks are complex and cannot meet the requirements for high-quality network services. Software Defined Network (SDN) is an important technology that enables a completely new approach in how we develop and manage networks. SDN divides the data plane and control plane and promotes logical centralization of network control so that the controller can schedule the data in the network effectively through OpenFlow protocol. In this paper, we simulate the two SDN controllers of Ryu and POX, and compare their latency and throughput performance under Simple-Tree-Based (STB) and Fat-Tree-Based (FTB) network topologies. An SDN networking model has been designed using a Mininet emulator, and the code for custom STB/FTB topology is executed in Python script. Simulation outcomes indicate that in latency mode Ryu controller exhibited better results than POX controller, making it more suitable for small-scale SDN deployments. From the throughput simulation, POX controller displayed better results than Ryu, showing that it is able to respond to requests more promptly under complex FTB traffic loads, but with more hardware resources utilization.


References | Cited By  «-- Click to see who has cited this paper

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[CrossRef] [Web of Science Times Cited 634] [SCOPUS Times Cited 861]


[2] N. Feamster, J. Rexford, E. Zegura, "The Road to SDN: an intellectual history of programmable networks", ACM SIGCOMM Computer Communication Review, vol. 44, no.2, April 2014,
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[6] A. Lara, A. Kolasani, B. Ramamurthy, "Network innovation using OpenFlow: A survey", IEEE Comm. Surveys Tutorials, vol. 16, issue 1, pp. 493-512, 2014,
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[CrossRef] [Web of Science Times Cited 40] [SCOPUS Times Cited 73]


[15] R. Khondoker, A. Zaalouk, R. Marx, K. Bayarou, "Feature-based comparison and selection of Software Defined Networking (SDN) controllers", 2014 World Congress on Computer Applications and Inf. Systems (WCCAIS), 2014,
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[16] S. Rowshanrad, V. Abdi and M. Keshtgari, "Performance evaluation of SDN controllers: Floodlight and OpenDayLight" IIUM Engineering Journal, vol. 17, no. 2, pp. 47-57, 2016.
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[17] M. P. Fernandez, "Comparing OpenFlow controller paradigms scalability: reactive and proactive", IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), 2013,
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[18] P. Bispo, D. Corujo and R. L. Aguiar, "A Qualitative and Quantitative assessment of SDN Controllers", International Young Engineers Forum (YEF-ECE), pp. 6-11, 2017,
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[20] B. Vengainathan, A. Basil, M. Tassinari, V. Manral, S. Banks, "Benchmarking Methodology for Software-Defined Networking (SDN) Controller Performance," IETF, RFC 8456, 2018, [Online] Available: Temporary on-line reference link removed - see the PDF document

[21] A. Shalimov, D. Zuikov, D. Zimarina, V. Pahskov, R. Smeliansky, "Advanced Study of SDN/OpenFlow Controllers," Proceedings of the Central Eastern European Software Engineering Conference CEE-SECR '13, no. 1, pp. 1-6, 2013,
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[22] H. M. Noman, M. N. Jasim, "POX Controller and Open Flow Performance Evaluation in Software Defined Networks (SDN) Using Mininet Emulator," 3rd International Conference on Sustainable Engineering Techniques (ICSET 2020), vol. 881, 2020,
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[23] C. Gomez, F. Gilabert, M. E. Gomez, P. Lopez, J. Duato, "Deterministic versus Adaptive Routing in Fat-Trees", IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 1-8, 2007,
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[25] I. Z. Bholebawa, R. K. Jha, U. D. Dalal, "Performance Analysis of Proposed Network Architecture: OpenFlow vs. Traditional Network" International Journal of Computer Science and Information Security, Part I, ISSN 1947-5500 vol. 14, no. 3, pp. 30-39, 2016

[26] M. Jarschel, F. Lehrieder, Z. Magyari and R. Pries, "A Flexible OpenFlow-Controller Benchmark", 2012 European Workshop on Software Defined Networking, pp. 48-53, 2012,
[CrossRef] [SCOPUS Times Cited 68]




References Weight

Web of Science® Citations for all references: 8,095 TCR
SCOPUS® Citations for all references: 11,276 TCR

Web of Science® Average Citations per reference: 300 ACR
SCOPUS® Average Citations per reference: 418 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-09 17:47 in 145 seconds.




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