COST PERFORMANCE OF SCALING APPLICATIONS ON THE CLOUD

Abstract

The inherent scaling capability and pay-per-use charging have led to the growth of cloud computing as a choice of compute resource infrastructure for a wide range of users from large corporations to individuals. While the inherent resource scaling on cloud has been well explored, the cost performance of scaling applications on cloud has received much less attention. Leveraging application scalability on inherently scalable cloud resources opens up new opportunities for cloud consumers to yield the maximum advantage from cloud. This thesis investigates the premise of scaling applications on cloud and its implications on cost performance. Motivated by Amdahl's fixed-workload scaling and Gustafson's fixed-time scaling for high performance computing, we propose fixed-cost scaling for cloud computing and investigate the implications of the proposed fixed-cost law under fixed-workload and fixed-time. Under fixed-cost application scaling, we address three key issues: large cloud resource configuration space, scaling application problem size, and scaling accuracy.