Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Mohamed, Omar M.
- Assessing a Real-time Adaptive Traffic Route Based on Ranking Software Defined Networking (SDN) Cluster of Controllers in a Datacenter
Abstract Views :63 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science, Faculty of Science, Minia University, EG
2 Computer Science Department, Faculty of Computers and Artificial Intelligence, University of Sadat City, EG
1 Department of Computer Science, Faculty of Science, Minia University, EG
2 Computer Science Department, Faculty of Computers and Artificial Intelligence, University of Sadat City, EG
Source
International Journal of Computer Networks and Applications, Vol 10, No 6 (2023), Pagination: 868-888Abstract
Software Defined Networking (SDN) is the new network model that uses the notion of centralized administration and control to promote network management. Although SDN offered many advantages to promote network performance, some challenges arose due to its architecture. A centralized controller must not constitute a single point of failure for the network to achieve high availability. This reveals the need for a Real-time fault tolerance mechanism. This mechanism aims to address potential failures by providing redundancy and failover capabilities within the network infrastructure. By distributing control and decision-making responsibilities across the cluster control, the system can continue to operate seamlessly by selecting the better controller by routing the traffic from the cluster to it even if one controller experiences a failure. This real-time fault tolerance mechanism plays a vital role in maintaining uninterrupted network operations and achieving the desired level of availability. This paper presents a Real-time Efficiently Adaptive Traffic Route RATR algorithm that ensures fault tolerance and load balancing which achieves high availability consistency based on real-time measurements of cluster members’ performance monitoring and records the results as votes. Then calculate the collected votes for each performance metrics load which are CPU, Memory, Network traffic, and Response time. Finally, run the proposed grading mechanism to elect the leader controller and his vices from among all cluster members. Extensive experiments are conducted to prove the effectiveness of RATR. The results show that RATR achieves an optimal performance not only on the network throughput but also on the delay and packet loss compared with Round Robin and SMCLBRT algorithms.Keywords
Software Defined Networking, Controller, Cluster, Traffic, Load-Balancing, Fault-Tolerance Throughput, RATR.Full Text
References
- H. Facchini, R. B. S. Perez, B. Roberti and R. Azcarate, "Experimental performance contrast between SDN and traditional networks," in 2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Valparaíso, Chile, 2021.
- H. Leqing, "How to Realize the Smooth Transition From Traditional Network Architecture to SDN," in 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), Harbin, China, 2020.
- Alghamdi, D. Paul and E. Sadgrove, "A RESTful Northbound Interface for Applications in Software Defined Networks," in 17th International Conference on Web Information Systems and Technologies (WEBIST 2021), 2021.
- Y. Li, D. Zhang, J. Taheri and K. Li, "SDN components and OpenFlow," in Big Data and Software Defined Networks, IET Digital Library, 2018, pp. 49-67.
- S. AZODOLMOLKY and O. Coker, Software-Defined Networking with OpenFlow, Second ed., Packt, 2017, pp. 248, ISNB:9781783984282.
- C. Lin, J. HU, G. Li and L. Cui, "A Review on the Architecture of Software Defined Network," Chinese Journal of Electronics, vol. 27, no. 6, pp. 1111-1117, 2018.
- Y. Zhanga, L. Cui, W. Wangc and Y. Zhanga, "A survey on software defined networking with multiple controllers," Journal of Network and Computer Applications, vol. 103, pp. 101-118, 2018.
- A. H. Alhilali and A. Montazerolghaem, "Artificial intelligence based load balancing in SDN: A comprehensive survey," Internet of Things, vol. 22, 2023.
- B. Yamansavascilar, A. C. Baktir, A. Ozgovdeb and C. Ersoya, "Fault tolerance in SDN data plane considering network and application based metrics," Journal of Network and Computer Applications, sciencedirect, vol. 170, 2020.
- N. Joshi and D. and Gupta, "A Comparative Study on Load Balancing Algorithms in Software Defined Networking," in Ubiquitous Communications and Network Computing, Springer International Publishing, 2019, pp. 142--150.
- J. Ali, R. H. Jhaveri, M. Alswailim and B.-h. Roh, "ESCALB: An effective slave controller allocation-based load balancing scheme for multi-domain SDN-enabled-IoT networks," Journal of King Saud University – Computer and Information Sciences, vol. 35, no. 6, 2023.
- J. Cui, Q. Lu, H. Zhong, M. Tian and a. L. Liu, "A Load-Balancing Mechanism for Distributed SDN Control Plane Using Response Time," IEEE Transactions on Network and Service Management, vol. 15, no. 4, pp. 1197-1206, 2018.
- A. Mantas and F. M. V. Ramos, "Rama: Controller Fault Tolerance in Software-Defined Networking Made Practical," 2019.
- H. Wang, L. X. H. Zhu, W. Xie and G. Lu, "Modeling and Verifying OpenFlow Scheduled Bundle Mechanism Using CSP," in 2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC), Tokyo, Japan, 2018.
- N. Katta, H. Zhang, M. Freedman and J. Rexford, "Ravana: Controller fault-tolerance software-defined networking," in In Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research, 2015.
- J. AliID, B.-h. Roh and S. LeeID, "QoS improvement with an optimum controller selection for software-defined networks," PLoS ONE, pp. 1-37, 2019.
- M. Priyadarsini, J. C. Mukherjee, P. B. S. Kumar, A. H. M. Jakaria and M. A. Rahman, "An adaptive load balancing scheme for software-defined network controllers," Computer Networks, Elsevier ScienceDirect, vol. 164, 2019.
- Y.-R. Chen, A. Rezapour, W.-G. Tzeng and S.-C. Tsai, "RL-Routing: An SDN Routing Algorithm Based on Deep Reinforcement Learning," IEEE Transactions on Network Science and Engineering, vol. 7, no. 4, pp. 3185-3199, 2020.
- H. Zhong, J. Fan, J. Cui, Y. Xu and Lu Liu, "Assessing Profit of Prediction for SDN controllers load balancing," Computer Networks, vol. 191, 2021.
- A. Mokhtar, X. Di, Y. Zhou, Z. M. A. Alzubair Hassan and S. Musa, "Multiple-level threshold load balancing in distributed SDN controllers," Computer Networks, vol. 198, pp. 108369 - 108385, 2021.
- C. Li, K. Jiang and Y. Luo, "Dynamic placement of multiple controllers based on SDN and allocation of computational resources based on heuristic ant colony algorithm," Knowledge-Based Systems, vol. 241, pp. 108330 - 108348, 2022.
- C. Li, S. Liang, J. Zhang, Q.-e. Wang and Y. Luo, "Blockchain-based Data Trading in Edge-cloud Computing Environment," Information Processing & Management, vol. 59, no. 1, pp. 102786-102808, 2022.
- K. Antevski, C. J. Bernardos, L. Cominardi, A. d. l. Oliva and Alain Mourad, "On the integration of NFV and MEC technologies: architecture analysis and benefits for edge robotics," Computer Networks, vol. 175, pp. 107274-107291, 2020.
- J. Ali and B.-h. Roh, "A Novel Scheme for Controller Selection in Software-Defined Internet-of-Things (SD-IoT).," Sensors, pp. 3591-3608, 2022.
- Z. C. S. O. O. Prince Boateng, "An Analytical Network Process model for risks prioritisation in megaprojects," International Journal of Project Management, vol. 33, no. 8, pp. 1795-1811, 2015.
- J. Ali, R. H. Jhaveri, M. Alswailim and Byeong-hee Roh, "ESCALB: An effective slave controller allocation-based load balancing scheme for multi-domain SDN-enabled-IoT networks," Journal of King Saud University - Computer and Information Sciences, vol. 35, no. 6, pp. 101566 - 101577, 2023.
- H. P. Enterprise, HPE VAN SDN Controller 2.7 REST API Reference, Hewlett Packard Enterprise Development LP, 2016.
- M. P. Contributors, "Mininet," Mininet, 2016. [Online]. Available: http://mininet.org/. [Accessed 2017]. How to cite this article:
- H. Packard, HPE VAN SDN Controller 2.7 Programming Guide, US: Hewlett Packard Enterprise Development LP, 2016.
- J. Dugan, S. Elliott, B. A. Mah, J. Poskanzer and K. Prabhu, "iperf.fr," iperf, [Online]. Available: https://iperf.fr/. [Accessed 2022].
- S. Kaur, K. Kumar, J. Singh and N. S. Ghumman, "Round-robin based load balancing in Software Defined Networking," in 2015 2nd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, 2015.
- M. S. Islam, M. Al-Mukhtar, M. R. K. Khan and a. M. Hossain, "A Survey on SDN and SDCN Traffic Measurement: Existing Approaches and Research Challenges," Eng, vol. 4, pp. 1071-1115, 2023.
- M. Omran, A. Alssaheli, Z. Z. Abidin, N. A. Zakaria and Z. A. Abas, "Implementation of Network Traffic Monitoring using Software Defined Networking Ryu Controller," WSEAS Transactions on Systems and Control, vol. 16, pp. 270-277, 2021.