Abstract
Consolidation of Virtual Machines (VMs) on the minimum number of physical servers has been recognized as a very efficient approach to increase the efficiency of virtualized data centers and save energy, as consolidation allows unloaded servers to be switched off or used to accommodate more load. The problem is so complex that centralized and deterministic solutions are useless in large data centers with hundreds or thousands of servers. This paper presents a self-organizing approach for the consolidation of VMs on two resources, CPU and RAM. Decisions on the assignment and migration of VMs are driven by probabilistic processes and are based on local information, which makes the solution simple to implement and scalable. Experiments on a real data center show that the approach rapidly consolidates the workload, and CPU-bound and RAM-bound VMs are balanced, so that both resources are exploited efficiently.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
