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Distributed & Scientific Computing

Many people carry a network capable device in their pocket.

The SocialNets project asks if human social structures can be harnessed to help adapt and improve networks?

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.


Research Expertise

Particular areas of strength and expertise in the School include:

  • Augmented and mixed reality
  • Cell planning and spectrum assignment for 3G and 4G mobile systems
  • Computational spectral theory and inverse problems
  • Computational steering
  • Data analysis and signal processing
  • Emergent paradigms for pervasive services using ambient networking
  • Grid-based, parallel & distributed computing and pervasive computing
  • Heuristic, meta-heuristic and evolutionary search for combinatorial optimization
  • Mesh networks
  • Naturally viewed 3D displays
  • Problem-solving and immersive visualization environments
  • Remote rendering
  • Stochastic modelling of information propagation in opportunistic communication networks
  • Wireless LAN systems, e.g. WiMax

Impact

  • Improving training of ultrasound scanner operators using visualisation and simulation
  • Automating e-Science workflows: the TRIANA workbench
  • Planning mobile phone networks using optimisation algorithms

Student Contributions

Recent successful PhD students have submitted the following theses:

  • I. Flood - Graph theoretic methods for radio equipment selection
  • K. Harwood - Investigation into Heuristic Methods of Solving Time Variant Vehicle Routing Problems
  • E. Al Shakarchi - Scalable Audio Processing Across Heterogeneous Distributed Resources: An Investigation into Distributed Audio Processing for Music Information Retrieval
  • I. Kelley - Secure Decentralized Data-Sharing in Dynamic Distributed Networks
  • A. Elwaer - Optimisation Techniques for Data Distribution in Volunteer Computing
  • M. Chorley - Performance engineering of hybrid message passing and shared memory programming on multi-core clusters

Current Grants & Research Projects

Project information
HolderProject TitleSourceValue (£Ks)
Professor O. Rana and Dr H. Li (School of Engineering)An innovative private cloud system to support multi-business collaborationKTP and Wakemans Ltd173.85
Professor O. Rana and Professor R. Rezgui (School of Engineering)Clouds4cooridnation: Cloud based project coordination in the AEC sectorTSB via BRE88.97
Dr L. Cipcigan, Professor N. Jenkins and Professor O.F. RanaEbbbs and flows of energy systems (EFES)EPSRC431.4
Professor O.F. Rana, Dr P. Burnap; Professor M. Levi and Professor M. Williams (Social Sciences); Professor K. Matthews (Business) and Dr V. Knight (Mathematics)Identifying and modelling victim, business, regulatory and malware behaviours in a changing cyberthreat lanscapeEPSRC1270.7
Professor B.M. Brown, Professor D.W.Walker and Professor M. Marletta (Maths)Inverse Problems for Magnetic Induction TomographyEPSC538.54
Professor J. Thomas and Professor D. Skilton (School of English, Communication, and Philosophy), Professor O. Rana and Professor P. RosinLost Visions: Retrieving the visual element of printed books from the nineteenth centuryAHRC439.96
Dr L Sloan, Dr M Williams and Dr P BurnapPublic perceptions of the UK food system: Public understanding and engagement, and the impact of crises and scaresESRC via NatCen Social Research36.87
Professor BM BrownResearch Network: Analysis on GraphsEPSRC124.77
Dr P. Burnap, Professor O.F. Rana, Dr L. CipciganSCADA Cyber Security LifecycleEADS UK227.67
Professor O.F.Rana and Dr P BurnapTo develop an intelligent (predictive), automated, enterprise-wide service-oriented remote IT asset managment system to reduce downtime and improve customer reporting and trustKTP and Circle IT Solutions LTD168.22

Recently Funded Research

The following projects have successfully completed:

  • Cregynog workshop on shrinking domains related topics
  • Designing Efficient Routes and Schedules for Public Transport Systems
  • Hate speech and social media: Understanding users, networks and information flows
  • Social media and prediction: Crime sensing, data integration and statistical modelling
  • The advanced medical image analysis and visualization unit