Energy Efficient Scheduling and Management for Large-Scale Services Computing Systems

With the increasing popularity of services published online, energy consumption of services computing systems is growing dramatically. Besides Quality of Service (QoS), energy efficiency has become an important issue and drawn significant attention. However, energy efficient request scheduling and service management for large-scale services computing systems face challenges because of the high dynamics and unpredictability of request arrivals. In this paper, we jointly consider the conflicting metrics of performance, queue congestion and energy consumption. We propose a distributed online scheduling and management algorithm which does not require any priori statistical knowledge of request arrivals. Mathematical analysis is conducted which demonstrates that our algorithm can achieve arbitrary tradeoff between performance and energy efficiency. Numerical and real trace data based experiments are carried out to validate the effectiveness of our algorithm in optimizing energy efficiency while stabilizing the system.