Energy effciency and performance of cloud data centers: which role can modeling play?

Abstract

Resource Virtualization and Load Balancing are main objectives to reduce the power consumption and to improve the performance of large data centers (DC). The management of Cloud Data Centers (CDC) requires an accurate planning and an efficient use of system resources in order to save energy consumption ("greening"), to provide Quality of Service (QoS), and to meet negotiated Service Level Agreements (SLA). This contribution addresses the question of modeling and the development of generic queuing models for energy-efficient use of resources for dynamic load balancing in virtualized CDCs. Performance models are developed for energy efficiency through automatic Server Consolidation, Dynamic Voltage and Frequency Scaling (DVFS) under Static Load Balancing; Dynamic Load Balancing can be achieved through Virtual Machine (VM) migrations. The analysis of such models provides quantitative performance figures upon which the system operation can be optimized with respect to guaranteed real-time performance and energy efficiency under prescribed SLAs.