13 papers · ranked by Valyu relevance
Ahmed Abdulhakim Al-Absi, Najeeb Abbas Al-Sammarraie, Wael Mohamed Shaher Yafooz, Dae-Ki Kang
MapReduce is the preferred cloud computing framework used in large data analysis and application processing. MapReduce frameworks currently in place suffer performance degradation due to the adoption of sequential processing approaches with little modification and thus exhibit underutilization of cloud resources. To…
Muhammad Idris, Shujaat Hussain, Muhammad Hameed Siddiqi, Waseem Hassan + 3 more
'Waseem Hassan' 'Hafiz Syed Muhammad Bilal' 'Sungyoung Lee' 'Christophe Antoniewski'] Large quantities of data have been generated from multiple sources at exponential rates in the last few years. These data are generated at high velocity as real time and streaming data in variety of formats. These characteristics give…
Yufei Gao, Yanjie Zhou, Bing Zhou, Lei Shi + 1 more
The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To…
Jianfang Cao, Hongyan Cui, Hao Shi, Lijuan Jiao + 1 more
A back-propagation (BP) neural network can solve complicated random nonlinear mapping problems; therefore, it can be applied to a wide range of problems. However, as the sample size increases, the time required to train BP neural networks becomes lengthy. Moreover, the classification accuracy decreases as well. To…
Qinghua Lu, Shanshan Li, Weishan Zhang, Lei Zhang
Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process…
Si Zheng, Xiangke Liao, Xiaodong Liu
In extreme scale data processing systems, fault tolerance is an essential and indispensable part. Proactive fault tolerance scheme (such as the speculative execution in MapReduce framework) is introduced to dramatically improve the response time of job executions when the failure becomes a norm rather than an…
Suzanne J Matthews, Tiffani L Williams
Background MapReduce is a parallel framework that has been used effectively to design large-scale parallel applications for large computing clusters. In this paper, we evaluate the viability of the MapReduce framework for designing phylogenetic applications. The problem of interest is generating the all-to-all…
Weiyu Fu, Lixia Wang
Considering that in the process of job scheduling, the cluster load should be prebalanced rather than remedied when the load is seriously unbalanced; therefore, in this paper, the task scheduling flow of the Hadoop cluster is analyzed deeply. On the Hadoop platform, a self-dividing algorithm is proposed for load…
Jianfang Cao, Lichao Chen, Min Wang, Hao Shi + 1 more
Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model.…
Wei Fang, V. S. Sheng, XueZhi Wen, Wubin Pan
In the atmospheric science, the scale of meteorological data is massive and growing rapidly. K-means is a fast and available cluster algorithm which has been used in many fields. However, for the large-scale meteorological data, the traditional K-means algorithm is not capable enough to satisfy the actual application…
Lukman Ab. Rahim, Krishna Mohan Kudiri, Shiladitya Bahattacharjee, Francisco Martínez-Álvarez
'Francisco Martínez-Álvarez'] The parallelisation of big data is emerging as an important framework for large-scale parallel data applications such as seismic data processing. The field of seismic data is so large or complex that traditional data processing software is incapable of dealing with it. For example, the…
Faten K. Karim, Sara Ghorashi, Salem Alkhalaf, Saadia H. A. Hamza + 3 more
'Anis Ben Ishak' 'S. Abdel-Khalek' 'Saeed Mian Qaisar'] As a new computing resources distribution platform, cloud technology greatly influenced society with the conception of on-demand resource usage through virtualization technology. Virtualization technology allows physical resource usage in a way that will enable…
Wenlei Liu, Sentang Wu, Zhongbo Wu, Xiaolong Wu
The novel contribution of this paper is to propose an incremental pose map optimization for monocular vision simultaneous localization and mapping (SLAM) based on similarity transformation, which can effectively solve the scale drift problem of SLAM for monocular vision and eliminate the cumulative error by global…