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Task scheduling in big data platforms: a systematic literature review
Abstract Context: Hadoop, Spark, Storm, and Mesos are very well known frameworks in both
research and industrial communities that allow expressing and processing distributed …
research and industrial communities that allow expressing and processing distributed …
Energy-aware scheduling of mapreduce jobs for big data applications
The majority of large-scale data intensive applications executed by data centers are based
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
on MapReduce or its open-source implementation, Hadoop. Such applications are executed …
A dynamic and failure-aware task scheduling framework for hadoop
Hadoop has become a popular framework for processing data-intensive applications in
cloud environments. A core constituent of Hadoop is the scheduler, which is responsible for …
cloud environments. A core constituent of Hadoop is the scheduler, which is responsible for …
A survey of big data machine learning applications optimization in cloud data centers and networks
This survey article reviews the challenges associated with deploying and optimizing big data
applications and machine learning algorithms in cloud data centers and networks. The …
applications and machine learning algorithms in cloud data centers and networks. The …
Apache hadoop yarn parameter configuration challenges and optimization
Apache Hadoop Yarn is an open source framework for distributed as well as local storage,
processing and analysis of big data on commodity hardware. It provides MapReduce …
processing and analysis of big data on commodity hardware. It provides MapReduce …
An efficient MapReduce scheduling scheme for processing large multimedia data
In this paper, we propose a scheduling scheme to minimize the deadline miss of jobs to
which deadlines are assigned when processing large multimedia data such as video and …
which deadlines are assigned when processing large multimedia data such as video and …
Incremental FP-Growth mining strategy for dynamic threshold value and database based on MapReduce
X Wei, Y Ma, F Zhang, M Liu… - Proceedings of the 2014 …, 2014 - ieeexplore.ieee.org
With the coming of the Big Data era, data mining has been confronted with new
opportunities and challenges. Some limitations are exposed when traditional association …
opportunities and challenges. Some limitations are exposed when traditional association …
Performance modeling for I/O‐intensive applications on virtual machines
Abstract Models for virtual machines running on cloud computing systems. Modeling system
behaviors of clouds is a grand challenge because the resource utilization in VMs is …
behaviors of clouds is a grand challenge because the resource utilization in VMs is …
An enhanced data-locality-aware task scheduling algorithm for hadoop applications
In general, Hadoop improves the task scheduling performance by determining data locality
based on the location in which the input splits and MapTask are executed. However, if an …
based on the location in which the input splits and MapTask are executed. However, if an …
A requirements specification framework for big data collection and capture
The ad hoc processes of data gathering used by most organizations nowadays are proving
to be inadequate in a world that is expanding with infinite information. As a consequence …
to be inadequate in a world that is expanding with infinite information. As a consequence …