Abstract
Reducing energy consumption has become a critical issue in today data centers. Reducing the number of required physical and Virtual Machines results in energy-efficiency. In this paper, to avoid the disadvantages of VM migration, a static VM placement algorithm is proposed which places VMs on hosts in a Worst-Fit-Decreasing (WFD) fashion. To reduce energy consumption further, the effect of job scheduling policy on the number of VMs needed for maintaining QoS requirements is studied. Each VM is modeled by an M/M/* queue in space-shared, time-shared, and hybrid job scheduling policies, and energy consumption of real-time as well as non-real-time applications is analyzed. Numerical results show that the hybrid policy outperforms space-shared and time-shared policies, in terms of energy consumption as well as Service Level Agreement (SLA) violations. Moreover, our non-migration method outperforms three different algorithms which use VM migration, in terms of reducing both energy consumption and SLA Violations.
Highlights
Ever-increasingly, companies move to the cloud to lower their budgets and reduce costs by benefiting from pooled hardware and software resources, delivered as IT services
These shared, on demand services are mainly offered in three forms: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS)
We show that taking the job scheduling policy into consideration and adopting hybrid policy instead of space-shared or time-shared can remarkably reduce the energy consumption while maintaining Service Level Agreement (SLA) conditions
Summary
Ever-increasingly, companies move to the cloud to lower their budgets and reduce costs by benefiting from pooled hardware and software resources, delivered as IT services. These shared, on demand services are mainly offered in three forms: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). In the scope of IaaS clouds (e.g., Amazon EC2, Microsoft Azure, and Google Compute Engine (GCE)), server virtualization is a key factor for elasticizing the data center by sharing computing resources between several users and simultaneously, isolating them from each other. Server virtualization benefits IaaS datacenters, in fundamental different ways [1]:
Sign-in/Register to view highlights & summary 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.
