Hungarian Academy of Sciences, Institute for Computer Science and Control (MTA SZTAKI)

Hungarian Academy of Sciences, Institute for Computer Science and Control
Budapest, 1518, Pf. 63.
mta sztaki
Research group:
Laboratory of Parallel and Distributed Systems (LPDS)
Prof. Péter Kacsuk
Budapest, 1518, Pf. 63.


Institution Background 

MTA SZTAKI (Hungarian Academy of Sciences, Institute for Computer Science and Control) is one of the largest IT research institutes in the Central European region. The Institute was founded in 1964. Its staff consists of more than 300 full-time employees, more than 200 with university diploma and more than 70 with scientific degrees. The Institute has significant experience in research, development and operation of information infrastructures (esp. web and grid services) being one of the largest regional service providers in this field. The Institute holds an ISO 9001:2000 Quality Certificate. MTA SZTAKI is a Fraunhofer Project Center, member of ERCIM and W3C and manager of the Hungarian W3C Office. Through numerous EU FP6 and FP7 projects, researchers of MTA SZTAKI contribute extensively to European scientific co-operation projects. Different groups within the institute work on projects for international and Hungarian companies, as General Electric, Knorr-Bremse AG., T-Com,  RICOH, GE Hungary, MOL Rt. – the Hungarian Oil Company, NASA- National Aeronautic and Space Administration (USA), ONR – Office of Naval Research (USA), Paks – the Hungarian Nuclear Power Station.


Research Group Background

The Laboratory of Parallel and Distributed Systems (LPDS) consists of 10 senior researchers with PhD’s and 12 research associates and it is led by Prof. Peter Kacsuk. The laboratory has more than twenty years of experience in delivering high quality research in the field of parallel programming, grid systems and Cloud computing. The laboratory has several successful products and service lines to aid the development of distributed applications on various distributed computing infrastructures (e.g., the gUSE/WS-PGrade portal series, the MTA SZTAKI Desktop Grid service). The laboratory is also the leader of the MTA SZTAKI Cloud project that offers IaaS facilities for the institute and plays a pilot role for a Cloud infrastructure able to serve the member institutes of the Hungarian Academy of Sciences. Researchers of the laboratory have co-authored numerous scientific papers in the field of Cloud computing focusing on the service level, inter-operation, federations, scalability and performance optimization of IaaS Clouds. The laboratory’s technologies act as an enabler for commercial (e.g., in the CloudSME project to support commercial companies to exercise Cloud computing facilities with customized portal based interfaces) and academic applications so they can easily utilize complex Cloud environments in a transparent way. The laboratory participated in and led numerous national and EU funded R&D projects like CloudSME, Clakk, SCI-BUS, IDGF-SP, ER-flow, EGI-InSPIRE, agINFRA, GLOBAL excursion, EDGI, DEGISCO, SHIWA, EDGeS, S-CUBE or ETICS-2.


Attila Csaba Marosiis a research fellow at the Laboratory of Parallel and Distributed Systems in MTA SZTAKI. He received his MSc. from the Budapest University of Technology and Economics in 2006. He started PhD studies there in 2009. His research interest includes the reliability and volatility aspects of volunteer computing and autonomic management of services in dynamic environments. He participated in many national (HAGRID, Web2Grid) and international (EGEE, CoreGrid, EDGeS, EDGI) research and development projects. He is the coauthor of more than 30 scientific papers.


Major Interest in Action Scientific Topics

  • Distributed computing: Volunteer and Desktop Grid computing, formal methods for describing workflows, membrane systems for workflow specification, scheduling parameter-study workflows and unconventional methods for enacting workflows;
  • Energy efficiency;
  • Cloud computing: Cloud federations,Virtual appliance delivery and Clouds and nature;
  • Sustainable data management.