An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers
Abstract
We target the problem of managing server power states in a Cloud Data Center (CDC) to jointly minimize electricity consumption and maintenance costs arising from the variation of power (and consequently temperature) on the server’s CPU. An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers We look in more detail at a set of virtual machines (VMs) and their CPU and memory requirements across a set of Time Slot (TSs).
Introduction
An Approach to Balance Maintenance Costs and Electricity Consumption in Cloud Data Centers We then model the electricity consumed by taking into account the costs of processing VMs on the servers, the costs of transferring data between VMs, and the costs of migrating VMs across the servers. We also use a material-based fatigue model to calculate the maintenance costs needed to repair the CPU as a result of the server power state variation over time.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
Conclusion
We targeted the problem of jointly managing maintenance costs and electricity consumption in a CDC. After showing that changing the power states of PSs has an impact on both the cost of failure management and energy consumption, we have formulated the OMEC problem with the goal of jointly managing the above-mentioned costs. Since the OMEC problem is NP-Hard, we have described the MECDC algorithm, which has beendesigned to wisely leverage the tradeoff between different costs,as well as taking into account their long term impact over time.
