Redefining in-network computing for compute-native 6G networks

About the Project

Supervisory Team: Doctor Aristide Akem and Professor Steve Gunn

6G networks will be compute-native, evolving from packet-forwarding infrastructures into distributed in-network computing platforms. This project seeks to extend the limits of in-network computing by redefining what computation can be performed within the network data path, and how such capabilities can be coordinated across edge and core networks.

In-network computing enables performing computation within the network infrastructure. Over the past decade, substantial progress has been made towards offloading compute to programmable data-plane devices such as switches and SmartNICs, demonstrating that data aggregation, filtering, machine learning inference, and lightweight processing can be embedded into packet-processing pipelines.

However, important challenges remain. Scalability, coordination across distributed domains, predictability under strict latency constraints, and trustworthiness in multi-tenant environments must be addressed before in-network computing can become a native architectural feature of 6G networks. A rigorous understanding of these limits, and principled methods for overcoming them, remains a critical gap.

This PhD project will systematically investigate the architectural and practical boundaries of in-network computing across mobile, edge, and core environments, and develop principled approaches to overcome them.

The project will characterise current constraints in data-path programmability, state management, synchronisation, and hardware capabilities, and design mechanisms that extend these capabilities while preserving performance guarantees, predictability, and verifiability.

The research will address three central questions:

• what are the fundamental scalability, programmability, and performance limits of current in-network computing platforms, and how can they be extended to support native integration into next-generation network architectures?
• how can distributed in-network functions be synchronised and coordinated across edge and core domains while maintaining predictable and bounded behaviour?
• what abstractions and programming models are required to enable secure, trustworthy, and multi-tenant deployment of in-network computing functions?

The project combines programmable networking, machine learning, distributed systems, and hands-on experimentation with modern networking hardware to help make in-network computing native to 6G and beyond.

You will join a dynamic team with collaborations across the UK and abroad, and aim to publish research outputs in leading venues such as INFOCOM, NSDI, CoNEXT, SIGCOMM, and IEEE/ACM Transactions on Networking.

Entry requirements

You must have a UK 2:1 honours degree, or its international equivalent.

Essential:

• demonstrable programming experience in Python or C/C++
• prior coursework or project experience in computer networking or mobile networks

Desirable:

• experience with programmable networking technologies such as P4, DPDK, eBPF, or XDP
• experience working with networking hardware (e.g. SmartNICs, switches, and FPGAs)
• experience with machine learning frameworks

Fees and funding

We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.

Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.

Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.

Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

How to apply

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Computer Science (7089)
• add name of the supervisor in section 2

Applications should include:

• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)

Contact us

Faculty of Engineering and Physical Sciences

If you have a general question, feps-pgr-apply@soton.ac.uk.

Project leader

For an initial conversation, a.t-j.akem@soton.ac.uk).