kFloWar-Information Retrieval from Cloud using Optimum Data Migration - Raval, Vishwas
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In this book, a novel technique kFloWar for job submission in Cloud environment is proposed and tested. kFloWar technique considers both cloudlet transfer time and file transfer time while selecting appropriate hosts for cloudlet (job) submission on distributed resources with an objective to minimize execution time and cost. As cloud computing itself is a bigger umbrella that is merged with different technologies. This complex integration is also having a bad impact on the performance of cloud environment. This work is aimed to improve the performance of cloud environment with Dynamic Resource…mehr

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Produktbeschreibung
In this book, a novel technique kFloWar for job submission in Cloud environment is proposed and tested. kFloWar technique considers both cloudlet transfer time and file transfer time while selecting appropriate hosts for cloudlet (job) submission on distributed resources with an objective to minimize execution time and cost. As cloud computing itself is a bigger umbrella that is merged with different technologies. This complex integration is also having a bad impact on the performance of cloud environment. This work is aimed to improve the performance of cloud environment with Dynamic Resource allocation Algorithm using Clustering. It arranges the virtual machines in cluster form before allocating them to the datacenters. This arrangement provides an efficient CPU utilization and load sharing among the datacenters, so the performance can be enhanced in some aspects. It has been proved through experiments that kFloWar algorithm is having better performance than the existing algorithms.
Autorenporträt
Vishwas è professore assistente di informatica e ingegneria presso l'Università M S di Baroda. Ha conseguito un diploma di laurea presso l'Università del Gujarat e un master in ingegneria presso l'IIT di Roorkee. Ha più di 16 anni di esperienza nel campo accademico, della ricerca e dello sviluppo. Ha pubblicato oltre 20 articoli di ricerca nell'area della Computer Vision, dell'Information Retrieval e del Machine Learning.