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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Cloud computing ensures access to shared resources and common infrastructure, offering services on demand over a network for operations to meet changing business needs. Scheduling is a prominent activity that is executed in a cloud computing environment. To increase cloud computing work load efficiency, tasks scheduling is performed to get maximum profit. In cloud, high communication cost prevents task schedulers from being applied in large scale distributed environments. Cloud environment system scheduling is NP-complete. To solve the NP complete and NP hard problems heuristic approaches are used. This study proposes a hybrid optimization based on Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for scheduling in cloud environments.
Dr. M.Sridhar. 2015. \u201cHybrid Genetic Swarm Scheduling for Cloud Computing\u201d. Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 15 (GJCST Volume 15 Issue B3): .
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: 106
Country: India
Subject: Global Journal of Computer Science and Technology - B: Cloud & Distributed
Authors: Dr. M.Sridhar (PhD/Dr. count: 1)
View Count (all-time): 279
Total Views (Real + Logic): 8194
Total Downloads (simulated): 2211
Publish Date: 2015 07, Fri
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Neural Networks and Rules-based Systems used to Find Rational and
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Cloud computing ensures access to shared resources and common infrastructure, offering services on demand over a network for operations to meet changing business needs. Scheduling is a prominent activity that is executed in a cloud computing environment. To increase cloud computing work load efficiency, tasks scheduling is performed to get maximum profit. In cloud, high communication cost prevents task schedulers from being applied in large scale distributed environments. Cloud environment system scheduling is NP-complete. To solve the NP complete and NP hard problems heuristic approaches are used. This study proposes a hybrid optimization based on Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for scheduling in cloud environments.
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