Provisioning, Placement and Pipelining Strategies for Data-Intensive Applications in Cloud Environments
Devarshi Ghoshal, Lavanya Ramakrishnan
Abstract
Devarshi Ghoshal, Lavanya Ramakrishnan
Abstract
Clouds are increasingly being used for running data-intensive scientific applications. Data-intensive science applications need performance, scalability and reliability. However, these can be hard to achieve in cloud environments. Intelligent strategies are required to obtain better performance, scalability and reliability on cloud platforms. In this paper, we propose a set of pipelining strategies to effectively utilize provisioned cloud resources. Our experiments on the ExoGENI cloud testbed demonstrates the effectiveness of our approach in increasing performance and reducing failures.
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Clouds are increasingly being used for running data-intensive scientific applications. Data-intensive science applications need performance, scalability and reliability. However, these can be hard to achieve in cloud environments. Intelligent strategies are required to obtain better performance, scalability and reliability on cloud platforms. In this paper, we propose a set of pipelining strategies to effectively utilize provisioned cloud resources. Our experiments on the ExoGENI cloud testbed demonstrates the effectiveness of our approach in increasing performance and reducing failures.
Key concepts: Cloud computing, Computer science, Testbed, Provisioning, Scalability, Distributed computing, Reliability (semiconductor), Set (abstract data type)