Distributed & Scientific Computing

Our research into Distributed and Scientific Computing considers a number of distinct aspects of distributed systems and high performance computing. The aim of this work is often to enhance collaboration and communication and to ensure the efficient use of resources in a wide variety of commercial and scientific applications.

Themes such as interdisciplinary collaboration, mobile computing, wireless network design and optimisation have led to important technological developments in a range of fields including medicine and scientific visualisation.

Technologies for Communication and Collaboration

Our main areas of focus investigate the application of distributed computing technologies to support collaboration. Technologies that solve problems through the composition of web-services and the exploitation of workflow are examples of the impact of our work for massive medical data management.

Using Grid related technologies for e-Science, we also specialize in the collaborative exploration of large datasets through visualization, innovative problem-solving environments and simulation methodologies. Our work also extends to supporting and exploiting distributed and mobile devices, for example through mobile peer-to-peer systems and opportunistic networking.

Intelligent Techniques for Problem Solving

Complex problems require intelligent solutions. Our expertise in this area develops algorithms and methodologies that can scale against hard combinatorial problems to provide optimized models and solutions for real-world applications. Recent successes have led to important developments in data analysis for signal processing through non-linear and probabilistic modeling.

Further applications include green logistics, scheduling, load-balancing, wireless network design and radio spectrum allocation. Latterly this research has led to automatic cellular network design and spectrum management systems for wireless broadband, 3G and 4G networks, Mesh and WiMax. Sophisticated techno-economic scenarios are often used in our computational modeling to aid intelligent decision making in commercial scenarios.