Title :
Analysis of K-means algorithm for VM allocation in cloud computing
Author :
Bramantyo Adrian;Lukman Heryawan
Author_Institution :
Department of Computer Science, Gadjah Mada University, Yogyakarta, Indonesia
Abstract :
Cloud computing is known as dynamic service providers using physical resource or virtualized on the internet. Virtual machine technology is used by cloud computing client who do not require dedicated server. Important challenge in cloud computing is resource management to improve utilization. Virtual machine allocation method is one of the way to improve resource utilization in cloud computing. This research used a framework cloud simulator CloudSim version 3.0 and K-means clustering algorithm is used for virtual machine allocation method. Virtual machine allocation method using K-means clustering algorithm compared with existing FIFO algorithm on CloudSim. The test consists of two scenarios, first scenario each datacenter only has a host and the second scenario each datacenter has two hosts. In both scenarios have same amount of work. The analysis result obtained from both scenario is virtual machine allocation method using K-means is better than FIFO in virtual machine CPU utilization by reducing idle time and performing load balancing virtual machine in each datacenter.
Keywords :
"Cloud computing","Virtual machining","Resource management","Clustering algorithms","Algorithm design and analysis","Computational modeling","Heuristic algorithms"
Conference_Titel :
Data and Software Engineering (ICoDSE), 2015 International Conference on
Print_ISBN :
978-1-4673-8428-5
DOI :
10.1109/ICODSE.2015.7436970