<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption</p></abstract>

Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption

Using a vision cognitive algorithm to schedule virtual machines

School of Basic Science Changchun University of Technology, Yan An Street 2005, 130012 Changchun, China

Steinbuch Center for Computing Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Using a vision cognitive algorithm to schedule virtual machines"}

Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality...

Using a vision cognitive algorithm to schedule virtual machines

Publicado en línea: 25 sept 2014

Páginas: 535 - 550

Recibido: 19 ago 2013

DOI: https://doi.org/10.2478/amcs-2014-0039

Palabras clave
cloud computing, vision cognitive algorithm, VM scheduling, simulation

© by Jiaqi Zhao

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Using a vision cognitive algorithm to schedule virtual machines

Publicado en línea: 25 sept 2014

Páginas: 535 - 550

Recibido: 19 ago 2013

DOI: https://doi.org/10.2478/amcs-2014-0039

Palabras clavecloud computing, vision cognitive algorithm, VM scheduling, simulation

© by Jiaqi Zhao

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Palabras clave
cloud computing, vision cognitive algorithm, VM scheduling, simulation