Professor Karim Djemame
- Position: Professor
- Areas of expertise: Distributed systems; cloud computing; energy efficiency; heterogeneous parallel architectures; performance evaluation
- Email: K.Djemame@leeds.ac.uk
- Phone: +44(0)113 343 6590
- Location: 3.25d Bragg Building
- Website: My Personal Site | LinkedIn | Googlescholar | Researchgate | ORCID
My research in distributed systems develops fundamental principles and practical methods for problems that are computationally challenging and/or require unusual kinds of computing resources. In particular, it focuses on Edge/Cloud/HPC-based services to enable organisations to efficiently manage their high-end computing resources with QoS support.
It is by definition multidisciplinary, applied and brings collaboration with specialists from both industry and academia. It involves the development of standards-based infrastructure components for job and resource management (including resource brokering, Service Level Agreements, middleware); energy efficiency (modelling and optimisation); heterogeneous computing.
I have chaired a number of international workshops at Leeds (UKPEW and VeCOS), and hosted conferences/workshops elsewhere (ISIIC, Scalcom, Service Level Agreements, Tools for an Energy Efficient Cloud, GECON). I am the co-founder of the Heterogeneous Hardware & Software Alliance (HH&S), an initiative undertaken by the TANGO (Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation) project. The alliance aims to join efforts of organisations interested in the development of future technologies and tools to advance and take full advantage of computing and applications using heterogeneous hardware.
I was awarded a PhD degree in 1999 from the University of Glasgow.
- Director of Research and Innovation
- Programme Manager Advanced Computer Science - Cloud Computing
Distributed systems; Cloud computing; Energy efficiency; Heterogeneous parallel architectures; Performance evaluation, Parallel and Distributed Simulation.
I am a member of the Distributed Systems and Services theme.
- EDS Recommissioning, NERC
- EDGNESS: Energy Efficiency, Edge and Serverless Computing (NGI Pointer 2 / EU)
- System Architectures for Future Supercomputing, Fujitsu
- TANGO: Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation (EU). (GitHub)
- Software Defined Networks – Newton Mobility Grant (Royal Society)
- ASCETiC: Adapting Service lifeCycle towards EfficienT Clouds (EU). (GitHub)
- EKT-SLA: Enterprise Knowledge Transfer – Service Level Agreements (EPSRC)
- STRAPP: Trusted Digital Spaces through Timely Reliable and Personalised Provenance (TSB/Innovate UK)
- OPTIMIS: Optimized Infrastructure Services (EU)
- ISQoS: Intelligent Scheduling for Quality of Service (EPSRC)
- GridPPT: Grid Performance Prediction Tool (EPSRC)
- AssessGrid - Advanced Risk Assessment and Management for Trustable Grids (EU)
- BROADEN: Business Resource Optimisation for Aftermarket & Design on Engineering Networks (DTI/Innovate UK)
- DAME: Distributed Aircraft Maintenance Environment (EPSRC)
- AQMCC: Active Queue Management in Computer Networks (Nuffield Foundation)
- AMOS: Analysis and Modelling of Optical Systems (EPSRC)
- TCP over ATM Networks. (EPSRC)
My research contributes to leveraging the transformative, innovative and collaborative potential of open source according to the EU open source software strategy.
A catalogue of open source software for heterogeneous computing (including programming models, middleware components, monitoring, accelerator sharing, device emulation, energy modelling, code profiling) is available on the Heterogeneity Alliance Web site.
PhD Students (2022)
- Abdullah Aljulayfi – QoS and energy-aware self-adaptive system for efficient resource management in an edge computing environment
- Reem Alqahtani – Hybrid access control model based on blockchain and machine learning for edge-IoT environment
- Zhengchang Hua – Decentralising Digital Twins / Edge Computing
- Shyi Chen – Resource Management in Edge Computing
- Latifah Alsalem – Application of Federated Machine Learning to support Quality of Service in Edge Computing
- Abdulaziz Alhindi – Serverless Computing and Energy Efficiency
- Dipl. Eng.
In session 2022-2023 I am module leader for COMP3211 Distributed Systems and COMP5123M Cloud Computing Systems.
Research groups and institutes
- Distributed Systems and Services