International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 13 Issue: 02 | Feb 2026
p-ISSN: 2395-0072
www.irjet.net
A REVIEW OF COMPARISON OF SDN (SOFTWARE-DEFINED NETWORKING) Vs. TRADITIONAL NETWORKING FOR TRAFFIC MANAGEMENT Shashank Yadav1, Mrs. Sahreen Hizab2 1Master of Technology, Computer Science and Engineering, Sagar Institute of Technology and Management,
Barabanki, India
2Assistant Professor, Department of Computer Science and Engineering, Sagar Institute of Technology and
Management, Barabanki, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The rapid growth of cloud computing, Internet of
and Border Gateway Protocol (BGP) to determine optimal paths (Medhi and Ramasamy, 2017). While this distributed paradigm ensures robustness, it introduces operational complexity and limited flexibility in dynamic traffic environments.
Things (IoT), multimedia services, and data-intensive applications has significantly increased the complexity of network traffic management. Traditional networking architectures rely on tightly coupled control and data planes, distributed routing protocols, and static configuration mechanisms, which often limit flexibility, scalability, and realtime adaptability. In contrast, Software-Defined Networking (SDN) introduces architectural decoupling, centralized control logic, and network programmability, enabling dynamic and fine-grained traffic engineering. This review paper provides a systematic comparison between SDN and traditional networking paradigms with specific emphasis on traffic management mechanisms, including congestion control, load balancing, Quality of Service (QoS) enforcement, scalability, and security considerations. Existing literature is critically analyzed to evaluate performance improvements, operational complexity, and deployment challenges associated with both approaches. The study synthesizes findings from experimental, simulation-based, and hybrid implementations to highlight architectural trade-offs and practical limitations. Furthermore, emerging trends such as AI-driven traffic optimization and hybrid SDN deployments are discussed. The review aims to offer a structured foundation for researchers and network designers in selecting appropriate traffic management strategies for modern and future network infrastructures.
1.1.1 Emergence of Software-Defined Networking Software-Defined Networking (SDN) emerged as a paradigm shift to address the limitations of conventional architectures. By decoupling the control plane from the data plane, SDN centralizes network intelligence within a programmable controller, enabling dynamic traffic engineering and simplified network management (Kreutz et al., 2015). The introduction of Open Flow as a southbound interface allowed standardized communication between controllers and forwarding devices (McKeown et al., 2008). This architectural abstraction facilitates network programmability, rapid policy deployment, and global traffic visibility, marking a significant departure from static, hardware-driven designs.
Key Words: Software-Defined Networking (SDN), Traditional Networking, Traffic Management, Traffic Engineering, Quality of Service (QoS), Network Scalability.
1. INTRODUCTION 1.1 Background: Paradigms
Evolution
of
Networking
Figure-1: Software-Defined Networking
1.2 Importance of Traffic Management in Modern Networks
The evolution of computer networking has been driven by the growing demand for scalability, reliability, and efficient data delivery. Early network architectures were primarily hardware-centric, where routing decisions and packet forwarding were tightly integrated within proprietary devices. Traditional networking relies on distributed control mechanisms, in which each router independently executes routing protocols such as Open Shortest Path First (OSPF)
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Impact Factor value: 8.315
Traffic management plays a pivotal role in ensuring optimal network performance, particularly in environments characterized by heterogeneous applications such as cloud services, real-time streaming, and Internet of Things (IoT) systems. Effective traffic management mechanisms regulate bandwidth allocation, congestion avoidance, and routing
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