A survey on vertical and horizontal scaling platforms for big data analytics

AH Ali - International Journal of Integrated Engineering, 2019‏ - publisher.uthm.edu.my
There is no doubt that we are entering the era of big data. The challenge is on how to store,
search, and analyze the huge amount of data that is being generated per second. One of the …

Twister2: Design of a big data toolkit

S Kamburugamuve, K Govindarajan… - Concurrency and …, 2020‏ - Wiley Online Library
Data‐driven applications are essential to handle the ever‐increasing volume, velocity, and
veracity of data generated by sources such as the Web and Internet of Things (IoT) devices …

High-performance flow classification using hybrid clusters in software defined mobile edge computing

M Abbasi, A Shokrollahi, MR Khosravi… - Computer …, 2020‏ - Elsevier
Abstract Mobile Edge Computing (MEC) provides different storage and computing
capabilities within the access range of mobile devices. This moderates the burden of …

Cognitive computational model using machine learning algorithm in artificial intelligence environment

S Liu, CV Spiridonidis, MA Khder - Applied Mathematics and Nonlinear …, 2022‏ - sciendo.com
In order to explore the application of machine learning algorithm to intelligent analysis of big
data in an artificial intelligence (AI) environment, make cognitive computing meet the …

Twister2: Tset high-performance iterative dataflow

P Wickramasinghe, S Kamburugamuve… - … Conference on High …, 2019‏ - ieeexplore.ieee.org
The dataflow model is gradually becoming the de facto standard for big data applications.
While many popular frameworks are built around this model, very little research has been …

Twister: Net-communication library for big data processing in hpc and cloud environments

S Kamburugamuve, P Wickramasinghe… - 2018 IEEE 11th …, 2018‏ - ieeexplore.ieee.org
Streaming processing and batch data processing are the dominant forms of big data
analytics today, with numerous systems such as Hadoop, Spark, and Heron designed to …

High performance dataframes from parallel processing patterns

N Perera, S Kamburugamuve, C Widanage… - … Conference on Parallel …, 2022‏ - Springer
The data science community today has embraced the concept of Dataframes as the de facto
standard for data representation and manipulation. Ease of use, massive operator coverage …

Task-parallel analysis of molecular dynamics trajectories

I Paraskevakos, A Luckow, M Khoshlessan… - Proceedings of the 47th …, 2018‏ - dl.acm.org
Different parallel frameworks for implementing data analysis applications have been
proposed by the HPC and Big Data communities. In this paper, we investigate three task …

Spark implementation of the enhanced Scatter Search metaheuristic: Methodology and assessment

XC Pardo, P Argüeso-Alejandro, P González… - Swarm and Evolutionary …, 2020‏ - Elsevier
Optimization problems arise nowadays in all disciplines, not only in the scientific area but
also in the field of engineering or economics, and in many others. Currently, challenging …

Simulation of 3D centimeter-scale continuum tumor growth at sub-millimeter resolution via distributed computing

DA Goodin, HB Frieboes - Computers in biology and medicine, 2021‏ - Elsevier
Simulation of cm-scale tumor growth has generally been constrained by the computational
cost to numerically solve the associated equations, with models limited to representing mm …