Behavioral Model for Cloud aware Load and Power Management
Schröder, Kiril and Nebel, Wolfgang
HotTopiCS '13: Proceedings of the 2013 international workshop on Hot topics in cloud services
Within the last few years, the development of data centers has been moving into high-grade flexible architectures that adapt to the needs (by means of virtualization). This flexibility can be used by load management methods to minimize the energy demand. Depending on quality of service and the hardware used, the application of a load and power management (LPM) results in a big dynamic range of the number of servers currently required. Previous energy models for data centers did not take into account this dynamic sufficiently and thus are not suitable for cloud data centers. Therefore, we present two contributions in this paper. First, we enhance an existing LPM for virtual machines, which has been designed for single data centers, enabling it to interact in flexible environments, for example in inter cloud LPM systems. Second, we develop a model which abstracts the behavior of the LPM concerning the server allocation. This model can be consulted for forecasts and obtains an average precision of 93 %.
4 / 2013
inproceedings
ACM
19-26
AC4DC
AC4DC - Adaptive Computing for Green Data Centers: Raise of energy efficiency through intelligent load balancing and infrastructure management, from the distributor to the user
AC4DC - Adaptive Computing for Green Data Centers: Raise of energy efficiency through intelligent load balancing and infrastructure management, from the distributor to the user
OFFIS Autoren
