BT is building a self-driving network that can detect its own breakdowns, reroute traffic, and repair itself without human intervention. Today’s digital infrastructure—the cables, exchanges, and data centres that carry phone calls, internet traffic, and business services—is largely managed by human engineers who respond to problems after they occur. As demand for capacity and new services grows, this reactive model becomes too slow and expensive. The network cannot easily adapt to unexpected disruptions or support novel services without costly physical upgrades. This programme aims to create a “digital twin” of the physical network—a software replica that continuously monitors the system’s state, predicts failures, and autonomously redeploys virtualised network functions to the safest locations. If a fibre cable is damaged or a server overheats, the network would detect the risk, analyse the impact on services, and take corrective action in real time. If successful, the UK’s digital backbone would become more resilient, cheaper to operate, and capable of supporting future services—such as holographic communications or massive sensor networks—without digging up roads or replacing hardware. The research is applied, not fundamental: it directly targets BT’s operational needs and aims to keep the UK competitive as a digital economy.
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This programme will forge the research required to underpin the next generation converged digital infrastructure for BT, creating a radically new technology architecture for autonomous operation of future networks and services. Digital infrastructure networks of the future will be highly reliable and resilient to disruptions through autonomous operations and will be able to cope with increasing demands on its capacity and types of services. These networks will be equipped with programmable and virtualised network functions that can be flexibly placed at specific network locations. New and unpredicted services will be capable of being supported without the need to make costly changes to the infrastructure at the physical level. The physical nodes of the infrastructure network will be represented digitally by a 'digital twin' or 'software agent' which will make them "autonomic" - i.e., the capability to perceive its state and environment, understand and predict its behaviour, and react to disruptions and opportunities autonomously with an aim to enhance customer experience. The network will be able to detect and predict possible disruptions, analyse the risk to service provision, make autonomous decisions regarding the (re)deployment of functions to least risky network locations and arrange remedial actions such as repair or replacement of risk-prone nodes. This will lead to new services, improved resilience of the network, better customer experiences and greater operational efficiency ensuring that the UK remains a leading digital economy. In order to realise this vision, the research carried out in this programme is structured around 5 challenges: Research Challenge 1: Agile Converged Infrastructure Systems Architecture. The fundamental question addressed here is "How to build an agile digital infrastructure that is amenable to autonomous operations?" This will be achieved through developments in new technologies such as MicroNFV and SDN. Research Challenge 2: Future Networks Operations and Services. The fundamental question addressed here is "How to ensure service reliability of the agile autonomic digital infrastructure?" This will be achieved by developing an automated service ecosystem capable of placing virtualised network functions at specific network locations. Research Challenge 3: Autonomic Knowledge Framework. This challenge addresses the question "How to enable autonomous operational ability for the digital infrastructure?" This is tackled by a multi-agent system architecture and through creating data sources that are intelligent. Research Challenge 4: Autonomous Diagnostics and Response. This challenge addresses the question "How can the digital infrastructure respond to disruptions autonomously?" This will be answered by developing novel automated change detection and statistical learning techniques. Research Challenge 5: Future Organisational Dynamics. The question addressed here is "How can the organisation exploit the autonomic agile capabilities of the digital infrastructure?" This is addressed by developing decision-support algorithms for risk-based function redeployment and predictive asset management.
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