Resource provisioning in Science Clouds: Requirements and challenges

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the needs of high-performance applications, such as local clusters, high-performance computing systems, and computing grids. Different workloads are needed from different computational models, and the cloud is already considered as a promising paradigm. The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads, hence, their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service provider supporting scientific applications

I/O Workload in Virtualized Data Center Using Hypervisor

Cloud computing [10] is gaining popularity as it’s the way to virtualize the datacenter and increase flexibility in the use of computation resources. This virtual machine approach can dramatically improve the efficiency, power utilization and availability of costly hardware resources, such as CPU and memory. Virtualization in datacenter had been done in the back end of Eucalyptus software and Front end was installed on another CPU. The operation of performance measurement had been done in network I/O applications environment of virtualized cloud. Then measurement was analyzed based on performance impact of co-locating applications in a virtualized cloud in terms of throughput and resource sharing effectiveness, including the impact of idle instances on applications that are running concurrently on the same physical host. This project proposes the virtualization technology which uses the hypervisor to install the Eucalyptus software in single physical machine for setting up a cloud computing environment. By using the hypervisor, the front end and back end of eucalyptus software will be installed in the same machine. The performance will be measured based on the interference in parallel processing of CPU and network intensive workloads by using the Xen Virtual Machine Monitors. The main motivation of this project is to provide the scalable virtualized datacenter