Grant: Strategic Projects - Group

Cloud computing platforms represent the fastest growing component of the ICT infrastructure, both in terms of computing resources and energy consumption. Clouds are characterized by a hierarchy of parallel computing, starting from networks of data centers to the multi-core server processors within a data center, and by the heterogeneity of applications, job sizes and hardware resources. Adaptive power and resource management are critical for improving the power efficiency of next-generation cloud computing platforms, while providing quality-of-service (QoS) guarantees to each user. Our research will address this challenge by adopting a unique cross-layer approach in which the cloud computing hardware and infrastructure is jointly optimized with data center and network-wide resource allocation and management policies. We will focus specifically on the scalability of the proposed solutions, given the increasingly distributed and parallel nature of cloud computing services, and on robustness to large variations in client-side service requests and changing infrastructure. The complexity of the adaptive power management problem, both at the node-level and at the system-level, scales with the degree of parallelism available on these platforms. Scalability represents an entirely new challenge that has not been adequately addressed before in the context of power management for parallel computing. Our research will involve modelling, analysis, and the development of a simulation infrastructure as well as design methodologies. The research will bring together techniques and models from networking, adaptive algorithms, scheduling techniques for multi-processor systems, and the development of simulators that span all layers of the system.