Computer Science @ University of St Andrews

University of St Andrews crest

Networks and distributed systems

  • Academics in robes with Vint Cerf
  • The Jack Cole building
  • First year lecture
  • MSc students in the lab
  • MSc students in the lab
  • Undergraduate tutorial
  • Blue sky thinking
  • MSc students enjoying a sunny day
  • MSc students at the summer BBQ
  • First year students in a lab-based exercise class
  • MSc students in the snow after November graduation
  • MSc students after graduation
  • Undergraduate students after summer graduation


We are a group with a broad range of interests, from communication protocols to systems architecture and applications. We have a very practical approach to research: we like to build things and to perform experiments. Current topics of activity include:

  • Distributed and autonomic systems is concerned with the design, implementation and understanding of distributed computer systems. A project in this area is H2O.
  • Network architecture and design examines network and application systems architecture for communication. This includes network protocols, new network architectures (for edge networks and hybrid edge systems), signalling & control, network monitoring & measurement, wireless and mobile systems and high-speed networking. We also consider issues of security, privacy and trust across the network architecture.
  • Distributed learning environments work has focused principally on the research, development and deployment of service-based distributed learning environments. Actual deployments with real users have provided fertile ground for Quality of Service analysis of highly interactive systems. The work has also been key in stimulating the study of service-based learning environments and their QoS as research topics, as evidenced by the FP5 Learning Grid NoE, and the FP6 Learning Grid Infrastructure IP.
  • Big Data Lab the goal of our research is to identify, engineer and evaluate innovative technologies that address current and future Big Data challenges. Our data-intensive research agenda is pursued by modelling, building and evaluating novel architectures and algorithms based on sound computer science theory.
Academic staff Research students Research staff