Optimization Algorithms in SDN: Routing, Load Balancing, and Delay Optimization

Author:

Tache (Ungureanu) Maria Daniela1ORCID,Păscuțoiu Ovidiu2ORCID,Borcoci Eugen1

Affiliation:

1. Doctoral School of Electronics, Telecommunications & Information Technology, National University of Science and Technology Polytechnica of Bucharest, Bd. Iuliu Maniu nr. 1-3, 061071 Bucharest, Romania

2. Department of Automatics and Information Technology, Transilvania University of Brașov, Bd. Eroilor 29, 500036 Brașov, Romania

Abstract

Software-Defined Networking is today a mature technology, which is developed in many networks and also embedded in novel architectures like 5G and 6G. The SDN control centralization concept brings significant advantages for management and control in SDN together with the programmability of the data plane. SDN represents a paradigm shift towards agile, efficient, and secure network infrastructures, moving away from traditional, hardware-centric models to embrace dynamic, software-driven paradigms. SDN is compliant also with the virtualization architecture defined in the Network Function Virtualization framework. However, SDN should cooperate seamlessly for some years with the distributed TCP/IP control developed during the years all over the world. Among others, the traditional tasks of routing, forwarding, load balancing, QoS assurance, security, and privacy should be solved. The SDN native centralization brings also some new challenges and problems which are different from the traditional distributed control IP networks. The algorithms and protocols usable in SDN should meet requirements like scalability, convergence, redundancy assurance, sustainability, and good real-time response, and allow orchestrated automation in enhancing network resilience and adaptability. This work presents a theoretical review of state-of-the-art SDN optimization techniques, offering a critical and comparative discussion of various algorithms having tasks such as routing (including dynamic ones), forwarding, load balancing and traffic optimization, and forwarding delay minimization. Attention is pointed to general algorithms which can offer pragmatic solutions for large systems or multiple metric routing.

Publisher

MDPI AG

Reference30 articles.

1. Li, J., Yang, L., Wang, J., and Yang, S. (2018, January 14–16). Research on SDN Load Balancing based on Ant Colony Optimization Algorithm. Proceedings of the IEEE 4th Information Technology and Mechatronics Engineering Conference (ITOEC), Chongqing, China.

2. Review of Load Balancing Mechanisms in SDN-Based Data Centers;Du;J. Comput. Commun.,2024

3. An overview of QoS-aware load balancing techniques in SDN-based IoT networks;Rostami;J. Cloud Comput.,2024

4. Kumar, N., and Prasad, R.V. (2019). A Comparative Study on Load Balancing Algorithms in Software Defined Networking. Ubiquitous Communications and Network Computing: Proceedings of the Second EAI International Conference, Bangalore, India, 8–10 February 2019, Springer Nature Switzerland AG.

5. An Algorithm for Solving Graph Coloring Problems Based on an Improved Ant Colony Optimization;Zhou;UPB Sci. Bull. Ser. C,2023

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3