The book examines virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of the cloud data center. The book also focuses on basic design principles and analysis of virtual machine placement techniques and tasks allocation techniques.
The book examines virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of the cloud data center. The book also focuses on basic design principles and analysis of virtual machine placement techniques and tasks allocation techniques.
Madhusudhan H. S. is an Associate Professor in the Department of Computer Science and Engineering at Vidyavardhaka College of Engineering, Mysuru, Karnataka, India. Satish Kumar T. is an Associate Professor in the Department of Computer Science and Engineering at BMS Institute of Technology and Management, Bengaluru, Karnataka, India. Punit Gupta is an Post Doc Fellow, School of Computer Science, University College Dublin, Dublin, Ireland. Dinesh Kumar Saini is a Full Professor at the School of Computing and Information Technology, Manipal University Jaipur, Jaipur, Rajasthan, India. Kashif Zia is a Research Associate at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, United Kingdom.
Inhaltsangabe
1. Introduction to Optimization in Cloud Computing. 2. Improve QoS and Resource Efficiency in Cloud Using Neural Network. 3. Machine Learning-Based Optimization Approach to Analyze Text-Based Reviews for Improving Graduation Rates for Cloud-Based Architectures. 4. An Energy-Aware Optimization Model Using a Hybrid Approach. 5. Fault Tolerant and Reliable Resource Optimization Model for Cloud. 6. Asynchronous Checkpoint/Restart Fault Tolerant Model for Cloud. 7. Fault Prediction Models for Optimized Delivery of Cloud Services. 8. Secured Transactions in Storage System for Real-Time Blockchain Network Monitoring System. 9. Service Scaling and Cost- Prediction-Based Optimization in Cloud Computing. 10. Cost- and Network-Aware Metaheuristic Cloud Optimization. 11. The Role of SLA and Ethics in Cost Optimization for Cloud Computing.
1. Introduction to Optimization in Cloud Computing. 2. Improve QoS and Resource Efficiency in Cloud Using Neural Network. 3. Machine Learning-Based Optimization Approach to Analyze Text-Based Reviews for Improving Graduation Rates for Cloud-Based Architectures. 4. An Energy-Aware Optimization Model Using a Hybrid Approach. 5. Fault Tolerant and Reliable Resource Optimization Model for Cloud. 6. Asynchronous Checkpoint/Restart Fault Tolerant Model for Cloud. 7. Fault Prediction Models for Optimized Delivery of Cloud Services. 8. Secured Transactions in Storage System for Real-Time Blockchain Network Monitoring System. 9. Service Scaling and Cost- Prediction-Based Optimization in Cloud Computing. 10. Cost- and Network-Aware Metaheuristic Cloud Optimization. 11. The Role of SLA and Ethics in Cost Optimization for Cloud Computing.
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