# Optimization Algorithms in SDN: Routing, Load Balancing, and Delay Optimization  
[PERSON] ([PERSON])  
1 Doctoral School of Electronics, Telecommunications & Information Technology, National University of Science and Technology Polytechnica of Bucharest, Bal. Juliu Maniu nr. 1-3, 061071 Bucharest, Romania 11 Doctoral School of Electronics, Telecommunications & Information Technology, National University of Science and Technology Polytechnica of Bucharest, Bal. Juliu Maniu nr. 1-3, 061071 Bucharest, Romania 11 Doctoral School of Electronics, Telecommunications & Information Technology, National University of Science and Technology Polytechnica of Bucharest, Bal. Virtualization implies a process of transforming physical network resources into virtual software entities, allowing multiple virtual instances to run independently on the same physical infrastructure. Network virtualization grants capabilities for virtual network creation (VLANs and VPNs) along with virtual network functions (VNFs) that are operating independently of the machine used as a host, contributing to efficient and flexible resource usage. Virtualization technologies are facilitating the isolation, allocation, and management of network resources, thus contributing to a faster, secure, and efficient service delivery. Integrating all three concepts described above (SDN, network orchestration, and virtualization), powerful frameworks can be created with increased network flexibility, scalability, and management efficiency. Used together, those technologies allow companies to dynamically deploy and manage their network resources, having capabilities to quickly adapt to business needs. This framework is the best approach when the problem of infrastructure modernization is considered because it offers operational agility, enhanced performance, and strong security, and supports trending and advanced technologies like 5G networks, cloud services, and IoT. This paper represents a bibliographic research that illustrates different theoretical approaches to how researchers have used algorithms to improve the way SDN networks work and transmit information, with the aim of increasing their efficiency, accuracy, and security. The article is structured in sections that aim to present various theoretical algorithmic approaches depending on the type of algorithms and their purpose, involving the use of sets of methods or algorithms with the role of bringing improvements in the way the SDN network works. These improvements may involve decreasing response times, adaptability on network conditions changing, or other metric improvements. We can thus observe that in the SDN sphere, things can and do evolve in a good direction for the networks of the future. While the existing literature addresses various algorithms applicable to SDN with a focus on performance enhancements and security-related metrics, an extensive review covering the wide range of algorithms like those discussed in this paper is significantly lacking. This paper has the topics organized into several key classes of algorithms applicable to SDN. Section 3.1 examines traditional and well-known algorithms used commonly within standard networks that were tested on SDN in order to emphasize if this class is suitable to be used in the SDN context. Section 3.2 follows and presents the class of heuristic algorithms that are suitable for solving more complex problems and the discussion goes along on implementation approaches and effectiveness in network operation optimization. Following this, Section 3.3 focuses on a topic that is benefitting increased attention in the last period, the Artificial Intelligence and Machine Learning algorithms, presenting their growing importance and applications in SDN for adaptive and predictive network management. Section 4 addresses the specific routing and traffic-related algorithms suitable for SDN environments. In Section 4.1, we presented algorithms related to latency optimization, designed to improve network responsiveness by minimizing delays.