Work place: Department of Computer Science, Canara Engineering College, Mangaluru, 575028, India
E-mail: demian.antony@gmail.com
Website:
Research Interests: Autonomic Computing, Image Compression, Image Manipulation, Image Processing
Biography
Dr. Demian Antony D’Mello is currently serving as the Professor & Head of Computer Science & Engineering Department at Canara Engg. College, Mangaluru. He received B.E in Computer Engineering from Mangalore University and M.Tech & Ph.D from NITK Surathkal. He has over 18 years of experience in education sector and over 45 publications in reputed international conferences/journals. He is a regular reviewer for many reputed journals and conferences. He also serves as an editorial board member for reputed journals. His areas of interest are web services, cloud computing, internet technologies and digital image processing.
By Shreenath Acharya Demian Antony D Mello
DOI: https://doi.org/10.5815/ijmecs.2018.12.04, Pub. Date: 8 Dec. 2018
The tremendous gain owing to the ubiquitous acceptance of the cloud services across the globe results in more complexity for the cloud providers by way of resource maintenance. This has a direct effect on the cost economy for them if the resources are not efficiently utilized. Most of the allocation strategies follow mechanisms involving direct allotment of VMs onto the servers based on their capabilities. This paper presents a VM allocation strategy that looks at VM placement by allowing server capacity to be partitioned into different classes. The classes are mainly based on the RAM and processing abilities which would be matched with VMs need. When the match is found the servers from this category are provisioned for the task executions. Based on the experimentation for various datacenter scenarios, it has been found that the proposed mechanism results in significant energy savings with reduced response time compared to the traditional VM allocation policies.
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