Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Collaborative cloud computing involves providing cloud services on globally distributed resources belonging to different organizations in a cooperative manner. Resource management and allocation in Collaborative Cloud is challenging because of the heterogeneity of the resources. The other challenge is guaranteeing the Quality of Service (QOS) and availability of these resources. Users’ resource demands have to be managed properly to ensure acceptable QOS. In this paper, we propose a method for effective management and allocation of resources using machine learning and using multi attribute tuning. The method has been simulated in cloud-sim as well as implemented on Amazon work space and results show that the proposed method performs better than reputation based algorithms.
Dr. Anirban Basu. 2015. \u201cA Dynamic Resource Allocation based on Multi Attributes Scoring in Collaborative Cloud Computing\u201d. Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 15 (GJCST Volume 15 Issue B4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 107
Country: India
Subject: Global Journal of Computer Science and Technology - B: Cloud & Distributed
Authors: Anitha N, Dr. Anirban Basu (PhD/Dr. count: 1)
View Count (all-time): 292
Total Views (Real + Logic): 8121
Total Downloads (simulated): 2111
Publish Date: 2015 10, Mon
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Neural Networks and Rules-based Systems used to Find Rational and
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Collaborative cloud computing involves providing cloud services on globally distributed resources belonging to different organizations in a cooperative manner. Resource management and allocation in Collaborative Cloud is challenging because of the heterogeneity of the resources. The other challenge is guaranteeing the Quality of Service (QOS) and availability of these resources. Users’ resource demands have to be managed properly to ensure acceptable QOS. In this paper, we propose a method for effective management and allocation of resources using machine learning and using multi attribute tuning. The method has been simulated in cloud-sim as well as implemented on Amazon work space and results show that the proposed method performs better than reputation based algorithms.
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