Wykaz publikacji wybranego autora

Michał Orzechowski, mgr inż.

pracownik inżynieryjno-techniczny

Wydział Informatyki, Elektroniki i Telekomunikacji
WIEiT-ki, *Katedra Informatyki


Identyfikatory Autora

ORCID: 0000-0002-8558-1283 połącz konto z ORCID

ResearcherID: brak

Scopus: 55054607600

PBN: 5e709472878c28a0473bd50c




1
  • A cloud-based data farming platform for molecular dynamics simulations
2
  • Bridging the gap between HPC and Cloud using HyperFlow and PaaSage
3
  • Cloud infrastructure automation for scientific workflows
4
  • Container-based architecture for resilient and reproducible scientific workflows
5
  • Cost-based optimization of execution of data farming experiments in PaaSage
6
  • Evaluation of container composition tools for multi-container distributed systems
7
  • Execution of scientific workflows on hybrid infrastructure, a case study of AWS Elastic Container Service in combination with AWS Lambda
8
  • Global access to legacy data-sets in multi-cloud applications with onedata
9
  • Manageability of deployment of multi-cloud scientific applications: data farming use-case
10
  • Model-based execution of scientific applications on cloud infrastructures: scalarm case study
11
  • Modeling of data farming application for multi-cloud execution
12
  • Molecular dynamics with HyperFlow and scalarm on the PaaSage platform
13
  • Onedata virtual filesystem for hybrid clouds
14
  • Parameter sweep and resources scaling automation in scalarm data farming platform
15
  • Reproducibility of computational experiments on Kubernetes-managed container clouds with HyperFlow
16
  • Scientific computing with application containers: onedata and hyperflow use cases
17
  • Scientific workflow management on hybrid clouds with cloud bursting and transparent data access
18
  • Storage systems control with decision trees for storage QoS provisioning
19
  • Towards open science with multi-cloud computing using Onedata
20
  • Towards scalable, semantic-based virtualized storage resources provisioning
21
  • Transparent data access for scientific workflows across clouds
22
  • Transparent deployment of scientific workflows across clouds – Kubernetes approach