Autonomic Power and Performance Management for Computing Systems

With the increased complexity of platforms, the growing demand of applications and data centers´ servers sprawl, power consumption is reaching unsustainable limits. The need to improved power management is becoming essential for many reasons including reduced power consumption & cooling, improved density, reliability & compliance with environmental standards. This paper presents a theoretical framework and methodology for autonomic power and performance management in e-business data centers. We optimize for power and performance (performance/watt) at each level of the hierarchy while maintaining scalability. We adopt mathematically-rigorous optimization approach minimizing power while meeting performance constraints. Our experimental results show around 72% savings in power as compared to static power management techniques and 69.8% additional savings with both global and local optimizations.