Cloud computing
A Sunyaev, A Sunyaev - … computing: Principles of distributed systems and …, 2020 - Springer
Cloud computing is an evolution of information technology and a dominant business model
for delivering IT resources. With cloud computing, individuals and organizations can gain on …
for delivering IT resources. With cloud computing, individuals and organizations can gain on …
Statistical characterization of business-critical workloads hosted in cloud datacenters
Business-critical workloads--web servers, mail servers, app servers, etc.--are increasingly
hosted in virtualized data enters acting as Infrastructure-as-a-Service clouds (cloud data …
hosted in virtualized data enters acting as Infrastructure-as-a-Service clouds (cloud data …
Exploring the potential of distributed computing continuum systems
Computing paradigms have evolved significantly in recent decades, moving from large room-
sized resources (processors and memory) to incredibly small computing nodes. Recently …
sized resources (processors and memory) to incredibly small computing nodes. Recently …
On inclusion of water resource management in Earth system models–Part 2: Representation of water supply and allocation and opportunities for improved modeling
A Nazemi, HS Wheater - Hydrology and Earth System Sciences, 2015 - hess.copernicus.org
Human water use has significantly increased during the recent past. Water withdrawals from
surface and groundwater sources have altered terrestrial discharge and storage, with large …
surface and groundwater sources have altered terrestrial discharge and storage, with large …
Data mining and life sciences applications on the grid
Data mining (DM) is increasingly used in the analysis of data generated in life sciences,
including biological data produced in several disciplines such as genomics and proteomics …
including biological data produced in several disciplines such as genomics and proteomics …
Distributed selection of continuous features in multilabel classification using mutual information
J González-López, S Ventura… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Multilabel learning is a challenging task demanding scalable methods for large-scale data.
Feature selection has shown to improve multilabel accuracy while defying the curse of …
Feature selection has shown to improve multilabel accuracy while defying the curse of …
A trichordal temporal approach to digital coordination
This paper develops a sociomaterial perspective on digital coordination. It extends
Pickering's mangle of practice by using a trichordal approach to temporal emergence. We …
Pickering's mangle of practice by using a trichordal approach to temporal emergence. We …
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 …
Large-scale, high-resolution agricultural systems modeling using a hybrid approach combining grid computing and parallel processing
The solution of complex global challenges in the land system, such as food and energy
security, requires information on the management of agricultural systems at a high spatial …
security, requires information on the management of agricultural systems at a high spatial …
Parallelization of a hydrological model using the message passing interface
With the increasing knowledge about the natural processes, hydrological models such as
the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with …
the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with …