This paper presents Exalt, a library that gives back to researchers the ability to test the scalability of today’s large storage systems. To that end, we introduce Tardis, a data representation scheme that allows data to be identified and efficiently compressed even at low-level storage layers that are not aware of the semantics and formatting used by higher levels of the system. This compressi...

Hadoop platform is widely being used for managing, analyzing and transforming large data sets in various systems. Two basic components of Hadoop are: 1) a distributed file system (HDFS) 2) a computation framework (MapReduce). HDFS stores data on simple commodity machines that run DataNode processes (DataNodes). A commodity machine running NameNode process (NameNode) maintains meta data informat...

The objective of comparing various dimensionality techniques is to reduce feature sets in order group attributes effectively with less computational processing time and utilization memory. reduction algorithms can decrease the dataset consisting a huge number interrelated variables, while retaining dissimilarity present as much possible. In this paper we use, Standard Deviation, Variance, Princ...

We model an apparent gravitational lens system HDFS 2232509–603243in the Hubble Deep Field South. The system consists of a blue V = 25 mag arc separated by 0. ′′9 from a red V = 22 mag elliptical galaxy. A mass distribution which follows the observed light distribution with a constant mass-to-light ratio can fit the arc component positions if external shear is added. A good fit is also obtained...

We model an apparent gravitational lens system HDFS 2232509–603243 in the Hubble Deep Field South. The system consists of a blue V = 25 mag arc separated by 0. 9 from a red V = 22 mag elliptical galaxy. A mass distribution which follows the observed light distribution with a constant mass-to-light ratio can fit the arc component positions if external shear is added. A good fit is also obtained ...

With the fast development of cloud computing and its wide application, data security plays an important role in cloud computing. This paper brought up a novel data security strategy based on artificial immune algorithm on architecture of HDFS for cloud computing. Firstly, we explained the main factors influence data security in cloud environment. Then we introduce HDFS architecture, data securi...

One performance bottleneck of distributed systems lies on the hard disk drive (HDD) whose single read/write head has physical limitations to support concurrent I/Os. Although the solid-state drive (SSD) has been introduced for years, HDDs are still dominant storage due to large capacity and low cost. This paper proposes a caching middleware that manages the underlying heterogeneous storage devi...

Big data makes cloud computing more and more popular in various fields. Video resources are very useful and important to education, security monitoring, and so on. However, issues of their huge volumes, complex data types, inefficient processing performance, weak security, and long times for loading pose challenges in video resource management. The Hadoop Distributed File System (HDFS) is an op...

Various sensors from airborne and satellite platforms are producing large volumes of remote sensing images for mapping, environmental monitoring, disaster management, military intelligence, and others. However, it is challenging to efficiently storage, query and process such big data due to the dataand computingintensive issues. In this paper, a Hadoop-based framework is proposed to manage and ...

The trace consists of cell information of about 29 days spanning across 700k jobs. This paper deals with statistical analysis of this cluster trace. Since the size of trace is very large, Hive which is a Hadoop distributed file system (HDFS) based platform for querying and analysis of Big data, has been used. Hive was accessed through its Beeswax interface. The data was imported into HDFS throu...