Add to ORKGCopyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ABSTRACT: In this research we propose a cluster for handling the existing processing problems in distributed environments. The volume of data transmitted through online service provider facility is already measured in terabytes. A single customer support outlet sends approximately 2 GB data in one day. Normal digital computers face instances like resources, cost and processing time for the processing of such large amount of data. Here we propose Cluster computing as solution of processing speed pro...
Distributed Computing System (DCS) computing plays an important role in computing world where proces...
Today data clustering has been widely applied to many practical applications like social network ana...
Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in appl...
Clustering is defined as the process of grouping a set of objects in a way that objects in the same ...
Data processing is used to uncover, transform, and classify information inside of data. Data-intensi...
Cluster computer systems assembled from commodity off-the-shelf components have emerged as a viable ...
The past few years have seen a major change in computing systems, as growing data volumes and stalli...
bzhana~hpl.hp.com Data clustering is one of the fundamental techniques in scientific data analysis a...
Although cluster environments have an enormous potential processing power, real applications that ta...
Today, a wide range of applications require higher computing power. A concept, known as cluster comp...
Amid a data revolution that is transforming industries around the globe, computing systems have unde...
There is a continual demand for greater computational power from computer systems than is currently...
The amount of information that must be processed daily by computer systems has reached huge quantiti...
Abstract. To cluster increasingly massive data sets that are common today in data and text mining, w...
Cluster became main platform as parallel and distributed computing structure for high performance co...
Distributed Computing System (DCS) computing plays an important role in computing world where proces...
Today data clustering has been widely applied to many practical applications like social network ana...
Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in appl...
Clustering is defined as the process of grouping a set of objects in a way that objects in the same ...
Data processing is used to uncover, transform, and classify information inside of data. Data-intensi...
Cluster computer systems assembled from commodity off-the-shelf components have emerged as a viable ...
The past few years have seen a major change in computing systems, as growing data volumes and stalli...
bzhana~hpl.hp.com Data clustering is one of the fundamental techniques in scientific data analysis a...
Although cluster environments have an enormous potential processing power, real applications that ta...
Today, a wide range of applications require higher computing power. A concept, known as cluster comp...
Amid a data revolution that is transforming industries around the globe, computing systems have unde...
There is a continual demand for greater computational power from computer systems than is currently...
The amount of information that must be processed daily by computer systems has reached huge quantiti...
Abstract. To cluster increasingly massive data sets that are common today in data and text mining, w...
Cluster became main platform as parallel and distributed computing structure for high performance co...
Distributed Computing System (DCS) computing plays an important role in computing world where proces...
Today data clustering has been widely applied to many practical applications like social network ana...
Dealing with large samples of unlabeled data is a key challenge in today’s world, especially in appl...