DocumentCode :
1773589
Title :
Virtual machine migration implementation in load balancing for Cloud computing
Author :
Razali, Rabiatul Addawiyah Mat ; Rahman, Ruhani Ab ; Zaini, Norliza ; Samad, M.
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear :
2014
fDate :
3-5 June 2014
Firstpage :
1
Lastpage :
4
Abstract :
The demand for Cloud computing usage is increasing day by day due to the advantages and facilities it offers. The fast growing rate of the usage of large-scale computing machines on cloud platform has resulted in increased consumption of energy and emission of carbon. Such negative effects should be curbed for a more environmental-friendly computing platform, e.g. a green cloud computing platform. Scheduling is one of the aspects that can be looked into in regards to the improvement of the whole cloud architecture, specifically in the scope of resource management. One of the important features that need to be optimized in regards to scheduling is the load balancing process that emphasizes on optimal resource utilization, maximum throughput, maximum response time and prevention of overload. One way to optimize the load balancing process is by implementing the migration of virtual machines across multiple hosts, in which utilization of CPU resources can be optimized. The appropriate use of two different classes of resources e.g. low-powered and high-powered machines based on their Million Instructions Per Second (MIPS) metrics, will lead to minimal process execution time if both types of resources are being efficiently used and effectively mapped to suitable types of processing. According to different machine performance, the migration of virtual machines will be computed based on the current CPU utilization following three different conditions, i.e. when the CPU usage reaches its 90%, 10% and 0% marker. Based on this idea, a general algorithm in activating the virtual machine migration is proposed, in which the overall load balancing process could be improved.
Keywords :
cloud computing; green computing; resource allocation; scheduling; virtual machines; CPU resource utilization; MIPS metrics; carbon emission; cloud architecture; energy consumption; environmental-friendly computing platform; green cloud computing platform; high-powered machines; large-scale computing machines; load balancing process; low-powered machines; maximum response time; maximum throughput; million instructions per second metric; minimal process execution time; optimal resource utilization; resource management; scheduling; virtual machine migration; Cloud computing; Computational modeling; Load management; Processor scheduling; Resource management; Servers; Virtual machining; CPU Utilization; Cloud Computing; Cloudsim; load balancing; virtual machine migration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent and Advanced Systems (ICIAS), 2014 5th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-4654-9
Type :
conf
DOI :
10.1109/ICIAS.2014.6869540
Filename :
6869540
Link To Document :
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