As the world ushers in the next wave of digital transformation powered by 5G, artificial intelligence (AI) and internet of things (IoT), software-defined networking (SDN) and its complementary technology, network functions virtualisation (NFV), stand at the forefront of innovation. These technologies are reshaping the networking domain by enabling operators and enterprises to decouple the functioning of networks from their physical infrastructure, thereby making them more efficient and agile.
The SDN architecture uses software-based controllers or application programming interfaces to communicate with underlying hardware infrastructure and direct network traffic. It enables operators to create and control virtual networks as well as manage traditional hardware through software. A prominent application of SDN is software-defined wide area network (SD-WAN), a virtual WAN architecture that allows enterprises to use various transport services such as multiprotocol label switching (MPLS), long term evolution (LTE) and broadband internet to securely connect users to applications. Unlike traditional WANs that backhaul all traffic to a central data centre, SD-WAN uses a centralised control function to intelligently direct traffic, improving application performance, enhancing the user experience and reducing IT costs.
NFV, meanwhile, virtualises traditional network functions such as load balancers, firewalls, subscriber policy management, and mobile radio access networks, running them as virtual network functions. This transformation creates more open and programmable networks through a centralised control layer, optimising network resources, reducing congestion, and increasing user capacity. Virtualised infrastructure helps operators lower both operating and capital expenses by using shared servers instead of dedicated appliances and reducing maintenance needs.
The adoption of SDN and NFV offers several significant benefits to operators and enterprises, such as reducing the time-to-market for new services, facilitating easy scaling of operations, enabling the delivery of personalised experiences to consumers, and reducing the energy footprint of networks. They enable operators to provide customisable and scalable network solutions to enterprise customers, supporting applications such as virtual private networks, unified communications and cloud connectivity. The ability to create dedicated network slices for IoT applications using SDN and NFV allows operators to cater to diverse IoT use cases such as smart homes and industrial IoT. SDN and NFV also allow greater control over network traffic, ensuring that critical applications receive the necessary bandwidth and low latency required for optimal performance. The adoption of these technologies further helps in the dynamic allocation of network resources based on real-time demand, thereby optimising resource utilisation and enhancing cost efficiency.
Market uptake
The SDN market has been experiencing considerable growth and is poised to expand from $26.8 billion in 2023 to $145.2 billion by 2032, with a CAGR of 20.9 per cent during this period. North America currently leads in SDN utilisation due to its early adoption of advanced networking technologies and the presence of major SDN vendors. In Europe, investments in digital infrastructure and cloud computing are fuelling substantial growth in the SDN and NFV market. The Asia-Pacific region is also expected to catch up in the near future, supported by the expansion of telecom networks and the proliferation of IoT. Meanwhile, the global market for NFV was worth $27.2 billion in 2023 and is estimated to reach $134.4 billion by 2032, with a projected CAGR of 18.9 per cent during 2024-32. Going forward, higher uptake of next-generation technologies, and the development of favourable standards and networking regulations are anticipated to fuel the adoption of NFV solutions.
Critical catalysts in next-generation networks
SDN and NFV are playing a crucial role in the adoption of next-generation technologies such as IoT, big data and cloud computing. These technologies require significant network infrastructure investments to manage their data volumes effectively. Additionally, rapid technological advancements quickly render hardware obsolete, resulting in recurring costs for operators. To this end, SDN and NFV enable operators to programmatically control all network elements through a unified interface, facilitating remote management from central locations. In the case of 5G, SDN provides centralised network management, enabling dynamic, programmable and automated network configurations by decoupling the control plane from the data plane. This capability is crucial for managing the complex and heterogeneous nature of 5G networks. Meanwhile, by replacing dedicated hardware appliances with software running on standard servers and allowing network functions to be virtualised and deployed on demand, NFV helps reduce the capital expenditure and operational expenditure associated with deploying 5G networks.
Furthermore, AI and IoT applications rely heavily on robust, adaptable and scalable network infrastructures. SDN’s dynamic network slicing allows the creation of multiple virtual networks tailored to specific IoT applications, such as smart cities, industrial automation and autonomous vehicles. Meanwhile, NFV’s ability to deploy network functions on standard hardware ensures that resources can be scaled up or down based on demand, facilitating the growth of AI and IoT ecosystems.
New innovations in SDN and NFV technologies
Over the past few years, there has been a significant push towards integrating SDN and NFV with cloud and edge computing. This integration is driven by the need to process data closer to the source, reducing latency and improving performance for applications such as autonomous driving, remote surgery and augmented reality. For instance, network functions are increasingly being designed as cloud-native applications, leveraging microservices and containerisation. This enhances the flexibility and scalability of network services, making them more adaptable to changing demands. Meanwhile, the deployment of SDN at the network edge enables efficient traffic management and resource allocation, crucial for supporting latency-sensitive applications. This also facilitates the creation of localised networks that can operate independently, ensuring continuity and reliability.
Moreover, AI and machine learning are being integrated into SDN and NFV frameworks to enable smarter, more autonomous network management. AI-driven analytics can predict network traffic patterns, optimise resource allocation and detect anomalies, enhancing overall network performance and security. Furthermore, AI algorithms can analyse data from network elements to predict potential failures and proactively initiate maintenance, minimising downtime and improving reliability. AI-driven orchestration tools enable automated deployment and management of network services, reducing the need for manual intervention and accelerating service delivery.
Key issues hindering widespread adoption
The growing uptake of SDN and NFV is part of a larger trend of decoupling software from dedicated hardware to build agile networks at significantly lower costs. However, a key challenge in scaling up the adoption of SDN and NFV is achieving interoperability and standardisation across different vendors and platforms. The lack of standardised interfaces and protocols can lead to compatibility issues, hindering seamless integration and deployment. Operators also face the risk of vendor lock-in if they rely on proprietary solutions, limiting their flexibility and increasing dependency on specific vendors. Moreover, operators cannot realise the optimal value of SDN and NFV until their operations support systems and business support systems are aligned with the new technologies.
On the technology front, the lack of mature technology, consensus on multiple open-source standardisation initiatives, and proven business cases continue to pose major hurdles. In some cases, virtualisation has been reported to lead to abnormal latency variations and significant throughput instability, even when the underlying network is only moderately utilised. Additionally, the transition to virtual networks raises security-related concerns. The centralised control plane in SDN can become a single point of failure, and the virtualisation of network functions can expose sensitive data to potential threats. Moreover, unlike conventional IT environments, NFV requires managing IT outside of the enterprise’s premises, removing an element of controllability and fuelling security concerns.
The transition towards all-virtualised and software-based frameworks has the potential to yield significantly higher returns on investments for operators and enterprises, along with a superior service quality experience for users compared to traditional hardware-driven networks. While telecom operators and enterprises globally are optimistic about the benefits that SDN and NFV bring to their network operations, they must grapple with the challenge of managing a combination of legacy networks and new virtualised networks until the migration to all-virtual networks is complete. Ongoing efforts by industry bodies are crucial in developing standardised frameworks and protocols to ensure interoperability and foster a multivendor ecosystem. Moreover, software by its very nature is less secure than hardware. Securing the SDN and NFV control planes with robust encryption and access control mechanisms is crucial for achieving widespread adoption.
