Towards efficient software deployment in the cloud using requirements decomposition

The major advancement in distributed and High Performance Computing (HPC) systems is the development and evolution of clouds, applications that operate these clouds, and services provided by them. Cloud computing applications are expected to facilitate running complex systems on data centers containing storage and computing units in the range of tens to hundreds of thousands of devices. Meeting the needs of cloud computing systems makes the software deployment process a challenging task. The challenge comes from difficulty in managing the tradeoffs over various dimensions, such as interaction, performance, and security while making deployment decisions. Making deployment decisions exceeds human capability in light of huge increase in computation/storage units in the clouds and software systems running on these clouds. Therefore, autonomic approaches to assist software designers in making the software deployment decisions are important. In this paper, we propose an approach based on clustering techniques for deploying software components on the cloud using requirements decomposition. The paper also demonstrates a validation study of the proposed approach with a case study