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Cloud Computing

Cloud computing is a style of computing in which, typically, resources scalable on demand are provided "as a service (aaS)" over the Internet to users who need not have knowledge of, expertise in, or control over the cloud infrastructure that supports them. The provisioning of cloud services can occur at the Infrastructural level (IaaS) or Platform level (PaaS) or at the Software level (SaaS). Cloud computing mainly forwards the utility computing model, where consumers pay on the basis of their usage. This research theme deals with several issues of cloud computing.

  • REMICS an EU FP7 project which is targeted at developing advanced model-driven methodology and tools for REuse and Migration of legacy applications to Interoperable Cloud Services. Within the project we are also dealing with building a framework for measuring performance and verifying scalability of enterprise applications running on the cloud.
  • Remodeling enterprise applications for the cloud
  • Migrating Traditional Databases to Cloud Scale Solutions: In recent years the amount of data stored and processed by different web applications has grown greatly. While splitting the input data and processing the pieces in parallel (e.g. MapReduce) on different nodes is an efficient solution for many applications, problems occur when trying to scale traditional relational database management systems (RDBMS). Recently, a new trend has emerged in data storage, commonly called NoSQL and proponents of NoSQL technologies argue that abandoning the relational model allows the databases to scale better horizontally and therefore is better suited for processing large amounts of data. Document-oriented, column-oriented and graph databases are all kinds of NoSQL solutions.






  • M. Vasar, S. N. Srirama, M. Dumas: Framework for Monitoring and Testing Web Application Scalability on the Cloud, Nordic Symposium on Cloud Computing & Internet Technologies (NORDICLOUD 2012), Co-located event at Joint 10th Working IEEE/IFIP Conference on Software Architecture & 6th European Conference on Software Architecture (WICSA/ECSA 2012), August 20-24, 2012. (Accepted for publication)
  • C. Paniagua, H. Flores, S. N. Srirama: Mobile Sensor Data Classification for Human Activity Recognition using MapReduce on Cloud, The 9th International Conference on Mobile Web Information Systems (MobiWIS 2012), August 27-29, 2012. Elsevier. (Accepted for publication)


  • V. Shor, N. Salnikov-Tarnovski, S. N. Srirama: Automated statistical approach for memory leak detection: case studies, In Proc. of First International Symposium on Secure Virtual Infrastructures (DOA-SVI 2011), October 17-19, 2011, pp. 633-640. LNCS 7045, Springer.
  • V. Shor, S. N. Srirama: A Statistical Approach For Identifying Memory Leaks In Cloud Applications, First International Conference on Cloud Computing and Services Science (CLOSER 2011), May 7-9, 2011, pp. 623-628. SciTePress. ISBN: 978-989-8425-52-2


  • G. Singer, I. Livenson, M. Dumas, S. N. Srirama, U. Norbisrath: Towards a model for cloud computing cost estimation with reserved resources, In Proc. of 2nd International ICST Conference on Cloud Computing, CloudComp 2010, October 26-28, 2010.