Big data analytics using cloud computing based frameworks for power management systems: Status, constraints, and future recommendations
Traditional parallel computing for power management systems has prime challenges such
as execution time, computational complexity, and efficiency like process time and delays in …
as execution time, computational complexity, and efficiency like process time and delays in …
The state of the art and taxonomy of big data analytics: view from new big data framework
Big data has become a significant research area due to the birth of enormous data
generated from various sources like social media, internet of things and multimedia …
generated from various sources like social media, internet of things and multimedia …
Enabling smart data: noise filtering in big data classification
In any knowledge discovery process the value of extracted knowledge is directly related to
the quality of the data used. Big Data problems, generated by massive growth in the scale of …
the quality of the data used. Big Data problems, generated by massive growth in the scale of …
[HTML][HTML] Analysis of hadoop MapReduce scheduling in heterogeneous environment
K Kalia, N Gupta - Ain Shams Engineering Journal, 2021 - Elsevier
Over the last decade, several advancements have happened in distributed and parallel
computing. A lot of data is generated daily from various sources, and this speedy data …
computing. A lot of data is generated daily from various sources, and this speedy data …
Distributed nearest neighbor classification for large-scale multi-label data on spark
Modern data is characterized by its ever-increasing volume and complexity, particularly
when data instances belong to many categories simultaneously. This learning paradigm is …
when data instances belong to many categories simultaneously. This learning paradigm is …
A new adaptive hybrid mutation black widow clustering based data partitioning for big data analysis
S Ravikumar, D Kavitha - Wireless Personal Communications, 2021 - Springer
In recent years, big data plays a significant role in data storage development in high
demand. The big data consists of a large number of datasets and it becomes trouble in …
demand. The big data consists of a large number of datasets and it becomes trouble in …
A critical analysis of apache hadoop and spark for big data processing
The emergence of big data processing platforms that can work globally in an integrated
manner and process the huge datasets efficiently has become very significant. A critical …
manner and process the huge datasets efficiently has become very significant. A critical …
QoS enabled cross-layer multicast routing over mobile ad hoc networks
Quality of group communication using mobile ad-hoc networks depends on various factors
like channel fading, signal quality, path loss, transmission and reception power of mobile …
like channel fading, signal quality, path loss, transmission and reception power of mobile …
Analyzing distributed Spark MLlib regression algorithms for accuracy, execution efficiency and scalability using best subset selection approach
Numerous studies emphasize accuracy in machine learning regression models, yet
scalability and execution efficiency are often overlooked, critical for large datasets or …
scalability and execution efficiency are often overlooked, critical for large datasets or …
LandQv2: A MapReduce-Based System for Processing Arable Land Quality Big Data
Arable land quality (ALQ) data are a foundational resource for national food security. With
the rapid development of spatial information technologies, the annual acquisition and …
the rapid development of spatial information technologies, the annual acquisition and …