Task scheduling in big data platforms: a systematic literature review

M Soualhia, F Khomh, S Tahar - Journal of Systems and Software, 2017 - Elsevier
Abstract Context: Hadoop, Spark, Storm, and Mesos are very well known frameworks in both
research and industrial communities that allow expressing and processing distributed …

Big data emerging technologies: A CaseStudy with analyzing twitter data using apache hive

A Bhardwaj, A Kumar, Y Narayan… - 2015 2nd International …, 2015 - ieeexplore.ieee.org
These are the days of Growth and Innovation for a better future. Now-a-days companies are
bound to realize need of Big Data to make decision over complex problem. Big Data is a …

[HTML][HTML] Experimental analysis in Hadoop MapReduce: a closer look at fault detection and recovery techniques

M Saadoon, SHA Hamid, H Sofian, H Altarturi… - Sensors, 2021 - mdpi.com
Hadoop MapReduce reactively detects and recovers faults after they occur based on the
static heartbeat detection and the re-execution from scratch techniques. However, these …

KPIs-based clustering and visualization of HPC jobs: a feature reduction approach

MS Halawa, RPD Redondo, AF Vilas - IEEE Access, 2021 - ieeexplore.ieee.org
High-Performance Computing (HPC) systems need to be constantly monitored to ensure
their stability. The monitoring systems collect a tremendous amount of data about different …

an anomaly detection method based on learning of “scores sequence”

D Li, S Shi, Y Zhang, H Wang, J Luo - … 21-23, 2018, Proceedings, Part II, 2018 - Springer
Anomaly detection is very important in the field of operation and maintenance (O&M).
However, in O&M, we find that direct use of the existing anomaly detection algorithms often …

Performance anomaly detection in HPC

MS Halawa - 2021 - investigo.biblioteca.uvigo.es
In recent years the demand for High-performance computing (HPC) data centers has
increased. HPC often consists of thousands of computing services. Given the high costs …

Adaptive Failure-Aware Scheduling for Hadoop

M Soualhia - 2018 - spectrum.library.concordia.ca
Given the dynamic nature of cloud environments, failures are the norm rather than the
exception in data centers powering cloud frameworks. Despite the diversity of integrated …

A study of an online dynamic workload prediction algorithm in the cloud environment

Y Wang, C Fan - Machinery, Materials Science and Engineering …, 2017 - taylorfrancis.com
With the foundation and inception of resource management, workload prediction technology
has always been the hot spot in the field of computing research. With the rapid development …