Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks

Main Article Content

Omar F. Hussain
Bilal R. Al-Kaseem
Omar Z. Akif

Abstract

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distributes network traffic to suitable paths, in addition to supervising link and path loads. A scenario with a minimum spanning tree (MST) routing algorithm and another with open shortest path first (OSPF) routing algorithms were employed to assess the SFSA. By comparison, to these two routing algorithms, the suggested SFSA strategy determined a reduction of 2% in packets dropped ratio (PDR), a reduction of 15-45% in end-to-end delay according to the traffic produced, as well as a reduction of 23% in round trip time (RTT). The Mininet emulator and POX controller were employed to conduct the simulation. Another advantage of the SFSA over the MST and OSPF is that its implementation and recovery time do not exhibit fluctuations. The smart flow steering agent will open a new horizon for deploying new smart agents in SDN that enhance network programmability and management.

Article Details

How to Cite
1.
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks. Baghdad Sci.J [Internet]. 2021 Mar. 10 [cited 2024 Mar. 28];18(1):0163. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4300
Section
article

How to Cite

1.
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks. Baghdad Sci.J [Internet]. 2021 Mar. 10 [cited 2024 Mar. 28];18(1):0163. Available from: https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4300

References

Braun W, Menth M. Software-Defined Networking Using OpenFlow: Protocols, Applications and Architectural Design Choices. Future Internet. 2014;6(2):302.

Gubbi J, Buyya R, Marusic S, Palaniswami M. Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions. FUTURE GENER COMP SY. 2013;29(7):1645 – 1660.

Al-Kaseem BR, Al-Dunainawi Y, Al-Raweshidy HS. End-to-End Delay Enhancement in 6LoWPAN Testbed Using Programmable Network Concepts. IEEE Internet of Things Journal (IOT-J). 2018 Nov 1;6(2):3070-86.

van der Meulen R. Analysts to Explore the Value and Impact of IoT on Business at Gartner Symposium / ITxpo 2015, November 8-12 in Barcelona, Spain; 2015. [Accessed on: Jun. 16, 2019]. http://www.gartner.com.

Chin WH, Fan Z, Haines R. Emerging technologies and research challenges for 5G wireless networks. IEEE Wireless Communications(IEEEWIRCOM). 2014 May 12;21(2):106-12.

Jara AJ, Zamora MA, Skarmeta A. Glowbal IP: An Adaptive and Transparent IPv6 Integration in the Internet of Things. Mob Inf Syst. 2012 Jul;8(3):177–197.

Akif OZ, Rodgers GJ, Al-Raweshidy HS. Protecting a Sensitive Dataset Using a Time Based Password in Big Data. In: 2017 Computing Conference; 2017. p. 871–879.

Al-Shabibi A, Martin B. MultiRoute - a Congestion-aware Multipath Routing Protocol. In: 2010 International Conference on High Performance Switching and Routing; 2010. p. 88–93.

Sabbeh A, Al-Dunainawi Y, Al-Raweshidy HS, Abbod MF. Performance Prediction of Software Defined Network Using an Artificial Neural Network. In: 2016 SAI Computing Conference (SAI); 2016. p. 80–84.

Sood K, Yu S, Xiang Y. Software-Defined Wireless Networking Opportunities and Challenges for Internet-of-Things: A Review. IEEE Internet of Things Journal (IOT-J). 2015 Sep 28;3(4):453-63.

Kreutz D, Ramos FMV, Veríssimo PE, Rothenberg CE, Azodolmolky S, Uhlig S. Software-Defined Networking: A Comprehensive Survey. Proceedings of the IEEE. 2015 Jan; 103(1):14–76.

Al-Kaseem BR, Al-Raweshidy HS. Enabling Wireless Software Defined Networking in Cloud Based Machine-to-Machine Gateway. In: 2016 8th Computer Science and Electronic Engineering (CEEC) (CEEC’16). Colchester, Essex, United Kingdom; 2016. p. 24–29.

He J, Song W. Achieving Near-Optimal Traffic Engineering in Hybrid Software Defined Networks. In: IFIP Networking Conference (IFIP Networking), 2015; 2015. p. 1–9.

Hasan H, Cosmas J, Zaharis Z, Lazaridis P, Khwandah S. Development of Performance of OSPF Network by Using SDN Concepts. In: Communications and Networking (BlackSeaCom), 2016 IEEE International Black Sea Conference on; 2016. p. 1–4.

Bakhshi T, Ghita B. User-Centric Traffic Optimization in Residential Software Defined Networks. In: 2016 23rd International Conference on Telecommunications (ICT); 2016. p. 1–6.

Jararweh Y, Al-Ayyoub M, Darabseh A, Benkhelifa E, Vouk M, Rindos A. SDIoT: a Software Defined Based Internet of Things Framework. J AMB INTEL HUM COMP. 2015;6(4):453–461.

Nguyen TT, Kim DS. Accumulative-Load Aware Routing in Software-Defined Networks. In: 2015 IEEE 13th International Conference on Industrial Informatics . 2015. p. 516–520.

Gholami M, Akbari B. Congestion Control in Software Defined Data Center Networks Through Flow Rerouting. In: 2015 23rd Iranian Conference on Electrical Engineering. 2015; p. 654–657.

Astaneh SA, Heydari SS. Optimization of SDN Flow Operations in Multi-Failure Restoration Scenarios. IEEE Transactions on Network and Service Management. 2016 Sept;13(3):421–432.

Fortz B, Thorup M. Optimizing OSPF/IS-IS weights in a changing world. IEEE journal on selected areas in communications (J-SAC) . 2002 Aug 7;20(4):756-67.

Wang SY, Wu CC, Chou CL. Constructing an Optimal Spanning Tree over a Hybrid Network with SDN and Legacy Switches. In: 2015 IEEE Symposium on Computers and Communication (ISCC). 2015; p. 502–507.

Cinkler T, Moldovan I, Kern A, Lukovszki C, Sallai G. Optimizing QoS Aware Ethernet Spanning Trees. In: 2005 1st International Conference on Multimedia Services Access Networks. 2005; MSAN ’05.; 2005. p. 30–34.

Akyildiz IF, Lee A, Wang P, Luo M, Chou W. A Roadmap for Traffic Engineering in SDN-OpenFlow Networks. Computer Networks. 2014;71:1 – 30.

Caria M, Jukan A, Hoffmann M. SDN partitioning: A centralized control plane for distributed routing protocols. IEEE Transactions on Network and Service Management(IEEE TNSM) . 2016 Jun 28;13(3):381-93.

Nakahodo Y, Naito T, Oki E. Implementation of smart-OSPF in hybrid software-defined network. In2014 4th IEEE International Conference on Network Infrastructure and Digital Content 2014 Sep 19 (pp. 374-378). IEEE.

Huang T. Path Computation Enhancement in SDN Networks ;. Master of Applied Science, Program of Computer Networks, Ryerson University, Toronto, Jan. 2015.

Similar Articles

You may also start an advanced similarity search for this article.