NDLI: A Private Cloud Instances Placement Algorithm Based on Maximal Flow Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Jian Guo Dongxu Han Gongxuan Zhang Kun Qian
Copyright Year	2015
Description	Author affiliation: Sch. of Electron. & Opt. Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China (Kun Qian) \|\| Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China (Jian Guo; Dongxu Han; Gongxuan Zhang)
Abstract	With the continuous development of cloud computing, bigger and bigger data processing run in the cloud computing environment. In generally, large companies or organizations have the demand of big data processing. However, these companies or organizations do not want to expose their business processes and data to third parties (Amazon, Google, etc.). The private cloud could meet their needs. In private cloud, if the instances of disk resource consuming are placed in the same physical node, clearly, the disk I/O bandwidth would be used up quickly that would affect the performance of the entire node seriously. In this paper, we propose an instances placement algorithm FFDL that based on the maximal flow method and would adopt the disk I/O load balancing strategy and reduce competition for the disk I/O bandwidth between instances. We have validated our approach by conducting a performance evaluation study on the open source privates cloud platform -- OpenStack. The results demonstrate that our algorithm has immense potential as it provides significant savings in computation time than the Greedy algorithm and demonstrates high potential for the improvement of disk I/O load balancing in the entire private cloud system for the big data processing.
Sponsorship	Tongji Univ.
Starting Page	59
Ending Page	62
File Size	1139873
Page Count	4
File Format	PDF
e-ISBN	9781467368506
DOI	10.1109/ICISCE.2015.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Greedy algorithms Algorithm design and analysis Cloud computing Maximal flow Instances placement Load management Private cloud Big data Virtual machining OpenStack Servers Disk I/O load balancing
Content Type	Text
Resource Type	Article

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