Challenges Towards Elastic Power Management in Internet Data Centers

1. Challenges Towards Elastic Power Management in Internet Data Centers Present by Sheng Cai

2. Data Centers • The number of servers and their resource consumptions grow exponentially. • The trend continues with the emergent of Cloud Computing • The cost of constructing multi-megawatt data centers is staggering.

3. Why elastic Macro Resource Management? • 1 The individual machine level (or micro-level) resource management is not enough. • 2 Resource demands in IDCs can change dramatically. • 3 Coordinated with physical resources such as power and cooling • 4 Fully utilize data center design capacities without wasting capital investments.

4. The Physical Infrastructure in Data Centers • 1 Power Distribution and Cost

5. The Physical Infrastructure in Data Centers • 2 Cooling

6. Elasticity of Data Center Computing • The demand for data center software services experience natural fluctuation and spikes. • The drastic demand variations require software applications in data centers to be elastic. • On the contrary to the slow cooling dynamics in data centers, the changes in computing activity are fast.

7. Elasticity of Data Center Computing • 1 Oversubscription of Resources • In an elastic computing paradigm, if one application’s resource requirement is low, one can find other services to fulfill the exceeded capacity by re-purposing the servers.

8. Elasticity of Data Center Computing • 2 Macro-Resource Management

9. Microfoundations for Macro-Resource Management 1 Device Architecture: Chip Multi-Processing (CMP) technology • Dynamic Voltage and Frequency Scaling(DVFS):CPU ,harddrive and main memory • Sleep (ON/OFF) Scheduling • Virtual Machine Management: VMM VPM • Cooling Management

10. A Few Research Directions 1 Modeling and Control • A holistic control and coordination framework for IDCs needs to deal with a variety of models, from continuous dynamics, to discrete events, to mode changes. • Given the temporal and spatial scale of the problem, statistical modeling, queuing theory, network information theory, and feedback control theories all play important roles.

11. A Few Research Directions 2 Cyber-Physical Co-Design • Co-design the software and the physical infrastructure to maximize resource utilization. • The challenge is the lack of consistent abstraction and modularity in computing and physical dynamics.

12. A Few Research Directions • 3 Data Management • How to structure the systems, what data to sense, how to compress raw data without losing key information, and what to share across system boundaries are the keys to achieve scalability.

13. Conclusion • Data centers are complex cyber-physical systems. • Power management in data centers has to be elastic, accommodating the dynamics in computing demands. • A coordination layer must take into account information from both cyber-activities and physical dynamics in data centers to make resource utilization follow the elasticity of software services.

14. Thank you!