Cloud computing is incredibly significant in recent technologies in IT sector. Various types of cloud computing services and applications are available via an internet connection. As cloud computing is serving millions of users simultaneously, it must have the ability to meet all users requests with high performance and guarantee of quality of service (QoS). The energy-aware scheduling algorithm is concentrated on both makespan and also in energy consumption. In this book a novel scheduling algorithm based on the factors of workload and job type to predict the makespan and also energy consumption. The motivation of this scheduling algorithm is to achieve energy-efficient green task scheduling and to optimize the scheduler that uses the sigmoid neural task predictor for the implementation. Resource provisioning in cloud computing is a major component that can improve the performance of a cloud system to a huge extent. High dimensionality and high variability in the cloud workloads pose major challenges in the allocation process. This part of the work presents an architecture that performs resource provisioning based on demand prediction and range-based resource allocation.
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Dr. VAISHNAVI P. completed her PhD in the Department of Computer Science and Eng, CEG Campus, Anna University, Chennai, and is working as Asst. Professor, Department of Computer Applications, Anna University. She has published more than 50 papers in reputed journals and has conducted sponsored conferences by AERB, Govt of India, BRNS and IGCAR.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Cloud computing is incredibly significant in recent technologies in IT sector. Various types of cloud computing services and applications are available via an internet connection. As cloud computing is serving millions of users simultaneously, it must have the ability to meet all users requests with high performance and guarantee of quality of service (QoS). The energy-aware scheduling algorithm is concentrated on both makespan and also in energy consumption. In this book a novel scheduling algorithm based on the factors of workload and job type to predict the makespan and also energy consumption. The motivation of this scheduling algorithm is to achieve energy-efficient green task scheduling and to optimize the scheduler that uses the sigmoid neural task predictor for the implementation. Resource provisioning in cloud computing is a major component that can improve the performance of a cloud system to a huge extent. High dimensionality and high variability in the cloud workloads pose major challenges in the allocation process. This part of the work presents an architecture that performs resource provisioning based on demand prediction and range-based resource allocation. 132 pp. Englisch. Bestandsnummer des Verkäufers 9786206769101
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Cloud computing is incredibly significant in recent technologies in IT sector. Various types of cloud computing services and applications are available via an internet connection. As cloud computing is serving millions of users simultaneously, it must have . Bestandsnummer des Verkäufers 1147894600
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Cloud computing is incredibly significant in recent technologies in IT sector. Various types of cloud computing services and applications are available via an internet connection. As cloud computing is serving millions of users simultaneously, it must have the ability to meet all users requests with high performance and guarantee of quality of service (QoS). The energy-aware scheduling algorithm is concentrated on both makespan and also in energy consumption. In this book a novel scheduling algorithm based on the factors of workload and job type to predict the makespan and also energy consumption. The motivation of this scheduling algorithm is to achieve energy-efficient green task scheduling and to optimize the scheduler that uses the sigmoid neural task predictor for the implementation. Resource provisioning in cloud computing is a major component that can improve the performance of a cloud system to a huge extent. High dimensionality and high variability in the cloud workloads pose major challenges in the allocation process. This part of the work presents an architecture that performs resource provisioning based on demand prediction and range-based resource allocation. Bestandsnummer des Verkäufers 9786206769101
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Taschenbuch. Zustand: Neu. Cloud Computing | An Efficient Load Balancing and Resource Provisioning in the Cloud Environment | Vaishnavi P. (u. a.) | Taschenbuch | Englisch | 2023 | Scholars' Press | EAN 9786206769101 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 127781364
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Cloud computing is incredibly significant in recent technologies in IT sector. Various types of cloud computing services and applications are available via an internet connection. As cloud computing is serving millions of users simultaneously, it must have the ability to meet all users requests with high performance and guarantee of quality of service (QoS). The energy-aware scheduling algorithm is concentrated on both makespan and also in energy consumption. In this book a novel scheduling algorithm based on the factors of workload and job type to predict the makespan and also energy consumption. The motivation of this scheduling algorithm is to achieve energy-efficient green task scheduling and to optimize the scheduler that uses the sigmoid neural task predictor for the implementation. Resource provisioning in cloud computing is a major component that can improve the performance of a cloud system to a huge extent. High dimensionality and high variability in the cloud workloads pose major challenges in the allocation process. This part of the work presents an architecture that performs resource provisioning based on demand prediction and range-based resource allocation.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 132 pp. Englisch. Bestandsnummer des Verkäufers 9786206769101
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