Energy-efficient hadoop for big data analytics and computing: A systematic review and research insights
As the demands for big data analytics keep growing rapidly in scientific applications and
online services, MapReduce and its open-source implementation Hadoop gained popularity …
online services, MapReduce and its open-source implementation Hadoop gained popularity …
Detecting straggler MapReduce tasks in big data processing infrastructure by neural network
Straggler task detection is one of the main challenges in applying MapReduce for
parallelizing and distributing large-scale data processing. It is defined as detecting running …
parallelizing and distributing large-scale data processing. It is defined as detecting running …
Early straggler tasks detection by recurrent neural network in a heterogeneous environment
KL Bawankule, RK Dewang, AK Singh - Applied Intelligence, 2023 - Springer
Heterogeneity is common in parallel and distributed environments used for extensive
computations such as MapReduce. Stragglers are the tasks that are running on inferior …
computations such as MapReduce. Stragglers are the tasks that are running on inferior …
Dockercap: A software-level power capping orchestrator for docker containers
A Asnaghi, M Ferroni… - 2016 IEEE Intl …, 2016 - ieeexplore.ieee.org
Internet of Things (IoT) is experiencing a huge hype these days, thanks to the increasing
capabilities of embedded devices that enable their adoption in new fields of application (eg …
capabilities of embedded devices that enable their adoption in new fields of application (eg …
A classification of Hadoop job schedulers based on performance optimization approaches
Job scheduling in MapReduce plays a vital role in Hadoop performance. In recent years,
many researchers have presented job scheduler algorithms to improve Hadoop …
many researchers have presented job scheduler algorithms to improve Hadoop …
Estimation accuracy on execution time of run-time tasks in a heterogeneous distributed environment
Distributed Computing has achieved tremendous development since cloud computing was
proposed in 2006, and played a vital role promoting rapid growth of data collecting and …
proposed in 2006, and played a vital role promoting rapid growth of data collecting and …
Recognizing mapreduce straggler tasks in big data infrastructures using artificial neural networks
M Farhang, F Safi-Esfahani - Journal of Grid Computing, 2020 - Springer
MapReduce framework is used for the distribution and parallelization of large-scale data
processing. This framework breaks a job into several MapReduce tasks and assigns them to …
processing. This framework breaks a job into several MapReduce tasks and assigns them to …
Optimizing speculative execution in spark heterogeneous environments
Z Fu, Z Tang - IEEE Transactions on Cloud Computing, 2019 - ieeexplore.ieee.org
The execution time of a stage is extended by a few slow running tasks in Spark computing
environments. To tackle this so-called straggler problem, Spark adopts speculative …
environments. To tackle this so-called straggler problem, Spark adopts speculative …
[PDF][PDF] Research on pattern analysis and data classification methodology for data mining and knowledge discovery
H Jiang, A Yang, F Yan, H Miao - International Journal of Hybrid …, 2016 - gvpress.com
A plethora of big data applications are emerging and being researched in the computer
science community which require online classification and pattern recognition of huge data …
science community which require online classification and pattern recognition of huge data …
An optimized speculative execution strategy based on local data prediction in a heterogeneous hadoop environment
Hadoop is a famous distributed computing framework that is applied to process large-scale
data." Straggling tasks" have a serious impact on Hadoop performance due to imbalance of …
data." Straggling tasks" have a serious impact on Hadoop performance due to imbalance of …