Server farms are playing an important role in the Internet infrastructure today. However, the increasing power consumption of server farms makes them expensive to operate. Thus, how to reduce the power consumed by server farms has become a important research topic. Power can be thought as a resource of system, just like traditional resources, and we can manage power via improved resource management strategies. In recent studies on power management, the system is attached with multiple states of different power consumption, and by switching among these states, power consumption can be made proportional to the work load. As different job scheduling policies will result in different performance and power consumption, an optimized policy with power as a factor can achieve a better tradeoff between performance and power consumption. In this paper, we summarize some familiar power management policies and propose a novel model using Stochastic Reward Nets(SRN). Based on this model, we analyze the performance and power consumption of different power management policies, and propose a novel cost-aware job scheduling algorithm.
['Yuan Tian', 'Chuang Lin', 'Min Yao']
Modeling and analyzing power management policies in server farms using stochastic Petri nets