An Efficient and Energy-Aware Cloud Consolidation Algorithm for Multimedia Big Data Applications

Symmetry

HeonChang Yu¹  JongBeom Lim²  Joon-Min Gil³ 

[1] Department of Computer Science & Engineering, Korea University, Seoul 02841, Korea;Department of Game & Multimedia Engineering, Korea Polytechnic University, Siheung-si, Gyeonggi-do 15073, Korea;School of Information Technology Engineering, Daegu Catholic University, Gyeongsan-si, Gyeongsangbuk-do 38430, Korea;

关键词: cloud consolidation;    virtual machine;    big data;    multimedia application;    cloud computing;   

DOI  :  10.3390/sym9090184

来源: DOAJ

【 摘 要 】

It is well known that cloud computing has many potential advantages over traditional distributed systems. Many enterprises can build their own private cloud with open source infrastructure as a service (IaaS) frameworks. Since enterprise applications and data are migrating to private cloud, the performance of cloud computing environments is of utmost importance for both cloud providers and users. To improve the performance, previous studies on cloud consolidation have been focused on live migration of virtual machines based on resource utilization. However, the approaches are not suitable for multimedia big data applications. In this paper, we reveal the performance bottleneck of multimedia big data applications in cloud computing environments and propose a cloud consolidation algorithm that considers application types. We show that our consolidation algorithm outperforms previous approaches.

【 授权许可】

Unknown