Minimalistic Adaptive Resource Management for Multi-tier Applications Hosted on Clouds

Cloud computing allows Web application owners to host their applications with low operational cost and enables them to scale applications to maintain performance based on traffic load and application resource requirements. However, for multi-tier Web applications, it is difficult to automatically identify the exact location of a bottleneck and scale the appropriate resource tier accordingly because multi-tier applications are complex and bottleneck patterns may be dependent on the specific pattern of workload at any given time. This Ph.D. dissertation aims to explore the possibilities to satisfy response time guarantees for multi-tier applications hosted on clouds using adaptive resource management with minimal hardware profiling and application-centric knowledge.