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Using a vision cognitive algorithm to schedule virtual machines

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Title: Using a vision cognitive algorithm to schedule virtual machines

Creator:

Zhao, Jiaqi ; Mhedheb, Yousri ; Tao, Jie ; Jrad, Foued ; Liu, Qinghuai ; Streit, Achim

Date:

2014

Resource Type:

artykuł

Contributor:

Abaev, Pavel - ed. ; Razumchik, Rostislav - ed. ; Kołodziej, Joanna - ed.

Subtitle:

.

Group publication title:

AMCS, Volume 24 (2014)

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 NP-hard 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.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Resource Identifier:

oai:zbc.uz.zgora.pl:78963

DOI:

10.2478/amcs-2014-0039

Pages:

535-550

Source:

AMCS, volume 24, number 3 (2014) ; click here to follow the link

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego

Subject and keywords:

cloud computing vision cognitive algorithm VM scheduling simulation

Object collections:

Last modified:

Apr 25, 2024

In our library since:

Apr 25, 2024

Number of object content hits:

54

All available object's versions:

https://zbc.uz.zgora.pl/repozytorium/publication/88764

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