Compare and contrast cloud computing cluster computing and grid computing
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Abstract: Cloud computing is rapidly growing as an alternative to conventional computing. However, it is based on models like cluster computing, distributed computing, utility computing and grid computing in general. This paper presents an end-to-end comparison between Cluster Computing, Grid Computing and Cloud Computing, along with the challenges they face. This could help in better understanding these models and to know how they differ from its related concepts, all in one go. It also discusses the long...
Introduction
High-performance computing (HPC) was once restricted to institutions that could afford the significantly expensive and dedicated supercomputers of the time. There was a need for HPC in small scale and at a lower cost which lead to cluster computing. The emergence of cluster platforms was driven by a number of academic projects, such as Beowulf [1], Berkeley NOW [2], and HPVM [3]. The popularity of the Internet and the availability of powerful computers and high-speed network technologies has changed the way computers are used. Grid computing originated in academia in the mid 1990s with an aim to facilitate users to remotely utilize idle computing power within other computing centers when the local one is busy [1]. Initially, it only referred to a compute grid and had a rather limited audience. However, after years of development the grid gained momentum and came to mean an effective way for coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations. Cloud computing, is a kind of computing model that came into existence around the end of 2007. It provides a pool of computing resources which the users can access through Internet. The basic principle of cloud computing is to shift the computing done from the local computer into the network [4]. This makes the enterprise use the resource which includes network, server, storage, application, service and so on that is required without huge investment on its purchase, implementation, maintenance rather use it for other significant purpose. Resources are requested on-demand with out any prior reservation and hence eliminates overprovisioning and improves resource utilization.
Introduction
High-performance computing (HPC) was once restricted to institutions that could afford the significantly expensive and dedicated supercomputers of the time. There was a need for HPC in small scale and at a lower cost which lead to cluster computing. The emergence of cluster platforms was driven by a number of academic projects, such as Beowulf [1], Berkeley NOW [2], and HPVM [3]. The popularity of the Internet and the availability of powerful computers and high-speed network technologies has changed the way computers are used. Grid computing originated in academia in the mid 1990s with an aim to facilitate users to remotely utilize idle computing power within other computing centers when the local one is busy [1]. Initially, it only referred to a compute grid and had a rather limited audience. However, after years of development the grid gained momentum and came to mean an effective way for coordinated resource sharing and problem solving in dynamic, multi-institutional virtual organizations. Cloud computing, is a kind of computing model that came into existence around the end of 2007. It provides a pool of computing resources which the users can access through Internet. The basic principle of cloud computing is to shift the computing done from the local computer into the network [4]. This makes the enterprise use the resource which includes network, server, storage, application, service and so on that is required without huge investment on its purchase, implementation, maintenance rather use it for other significant purpose. Resources are requested on-demand with out any prior reservation and hence eliminates overprovisioning and improves resource utilization.
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Unlike cluster or grid computing, where the emphasis is on the computation power to solve problem, cloud computing is concerned with the provisioning of services on demand. These services may include software applications, development tools, or even infrastructure.
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