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خانه مقالات مقالات کامپیوتر هادوپ A security framework in G-Hadoop for big data computing across distributed Cloud data centres
g-hadoop_software_architecture

A security framework in G-Hadoop for big data computing across distributed Cloud data centres

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MapReduce is regarded as an adequate programming model for large-scale data-intensive applications. The Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks on a cluster system.

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ABSTRACT

MapReduce is regarded as an adequate programming model for large-scale data-intensive applications. The Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks on a cluster system. G-Hadoop is an extension of the Hadoop MapReduce framework with the functionality of allowing the MapReduce tasks to run on multiple clusters. However, G-Hadoop simply reuses the user authentication and job submission
mechanism of Hadoop, which is designed for a single cluster. This work proposes a new security model for G-Hadoop. The security model is based on several security solutions such as public key cryptography and the SSL protocol, and is dedicatedly designed for distributed environments. This security framework simplifies the users authentication and job submission process of the current G-Hadoop implementation with a single-signon approach. In addition, the designed security framework provides a number of different security mechanisms to protect the G-Hadoop system from traditional attacks

INTRODUCTION
Today, data explosion is commonly observed in various scientific and social domains, such as GeoScience, Life Science,High Energy and Nuclear Physics, as well as Materials and Chemistry. Modern scientific instruments, the Web, and simulation facilities are producing huge data in the range of several petabytes. Currently, MapReduce [3] is commonly used for processing such big data. With a Map and a Reduce function, MapReduce provides simple semantics for users to program data analysis tasks in the code. Additionally, the parallelism in MapReduce is automatically done by a runtime framework which is especially friendly for application developers,

Publisher : ELSEVIER

Year:2014

By:Jiaqi Zhao a, Lizhe Wang b , Jie Tao c, Jinjun Chen d,∗, Weiye Sun c, Rajiv Ranjan e, Joanna Kołodziej f, Achim Streit c, Dimitrios Georgakopoulos

File Information:Language English/15 Page/Size:491 K

Download:click

ناشر: ELSEVIER

سال :2014

کاری از :Jiaqi Zhao a, Lizhe Wang b , Jie Tao c, Jinjun Chen d,∗, Weiye Sun c, Rajiv Ranjan e, Joanna Kołodziej f, Achim Streit c, Dimitrios Georgakopoulos

اطلاعات فایل:زبان انگلیسی/15 صفحه/حجم:491 K

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