Title :
A neural network based framework for apache YARN
Author :
Nivash, J.P. ; Raj, Ebin Deni ; Babu, L. D. Dhinesh ; Nirmala, M.
Author_Institution :
Sch. of Inf. Technol. & Eng., VIT Univ., Vellore, India
Abstract :
Hadoop has become the most used framework for data intensive processes such as mapreduce. Business intelligence and technology forecasting has played a big part in enhancing the popularity of Hadoop framework. In this paper we have proposed an improvement for apache Hadoop yarn (also known as Hadoop 2.0) architecture. Container nodes, application master, resource manager and the pool of resources are arranged and used in a more efficient way in this framework. We are proposing two new algorithms for selection of application master and for selection of container nodes.
Keywords :
data handling; neural nets; parallel processing; Hadoop 2.0; Hadoop framework; MapReduce; apache Hadoop yarn architecture improvement; application master selection; business intelligence; container node selection; data intensive processes; neural network based framework; resource manager; resource pool; technology forecasting; Algorithm design and analysis; Business; Containers; Databases; Educational institutions; Security; Yarn; YARN; application master; containesr; hadoop; mapreduce;
Conference_Titel :
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3835-3
DOI :
10.1109/ICICES.2014.7033783
