DocumentCode :
2352337
Title :
Using of Machine Learning into Cloud Environment (A Survey): Managing and Scheduling of Resources in Cloud Systems
Author :
Hormozi, Elham ; Hormozi, Hadi ; Akbari, Mohammad Kazem ; Javan, Morteza Sargolzai
Author_Institution :
Comput. Eng. & Inf. Technol., Mazandaran Univ. of Sci. & Technol., Babol, Iran
fYear :
2012
fDate :
12-14 Nov. 2012
Firstpage :
363
Lastpage :
368
Abstract :
Cloud computing is a model for delivering information technology services in which resources are retrieved from the internet through web-based tools and applications, rather than a direct connection to a server. Many companies, such as Amazon, Google, Microsoft and so on, are developing cloud computing systems and enhancing their services to provide for a larger amount of users. This technology holds a vast scope of using the various aspects of machine learning for increased performance and solving some of the challenges in front of the research community. in this survey, we investigate the effects using the concepts of machine learning on cloud environments, e.g. automated resource allocation mechanism, intelligently managing and allocating resources with SmartSLA, resources scheduling, etc.
Keywords :
cloud computing; learning (artificial intelligence); resource allocation; scheduling; Amazon; Google; Internet; Microsoft; SmartSLA; Web based tools; automated resource allocation; cloud computing systems; cloud environments; cloud systems; information technology services; machine learning; resources scheduling; Cloud computing; Computational modeling; Computers; Machine learning; Processor scheduling; Resource management; Time factors; allocating resource; cloud computing; intelligenty managing; machine learning; performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2012 Seventh International Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4673-2991-0
Type :
conf
DOI :
10.1109/3PGCIC.2012.69
Filename :
6362996
Link To Document :
بازگشت