A novel data placement strategy for data-sharing scientific workflows in heterogeneous edge-cloud computing environments

X Du, S Tang, Z Lu, J Wet, K Gai… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
The deployment of datasets in the heterogeneous edge-cloud computing paradigm has
received increasing attention in state-of-the-art research. However, due to their large sizes …

Scientific workflows in IoT environments: a data placement strategy based on heterogeneous edge-cloud computing

X Du, S Tang, Z Lu, K Gai, J Wu… - ACM Transactions on …, 2022 - dl.acm.org
In Industry 4.0 and Internet of Things (IoT) environments, the heterogeneous edge-cloud
computing paradigm can provide a more proper solution to deploy scientific workflows …

A novel workflow-level data placement strategy for data-sharing scientific cloud workflows

X Li, L Zhang, Y Wu, X Liu, E Zhu, H Yi… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Cloud computing can provide a more cost-effective way to deploy scientific workflows than
traditional distributed computing environments such as cluster and grid. Due to the large …

Effective data placement for scientific workflows in mobile edge computing using genetic particle swarm optimization

Z Chen, J Hu, G Min, X Chen - Concurrency and Computation …, 2021 - Wiley Online Library
Mobile edge computing (MEC) necessitates cost‐effective deployment for executing
scientific workflows with different tasks and datasets, which provides computing, storage and …

Optimizing semantic annotations for web service invocation

K Huang, J Zhang, W Tan, Z Feng… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Semantic annotations play an important role in semantics-aware service discovery,
recommendation and composition. While existing approaches and tools focus on facilitating …

Scientific workflows in heterogeneous edge-cloud computing: A data placement strategy based on reinforcement learning

X Du - arXiv preprint arXiv:2205.07131, 2022 - arxiv.org
The heterogeneous edge-cloud computing paradigm can provide an optimal solution to
deploy scientific workflows compared to cloud computing or other traditional distributed …

Optimal data placement for data-sharing scientific workflows in heterogeneous edge-cloud computing environments

X Du, S Tang, Z Lu, K Gai, J Wu, PCK Hung - arXiv preprint arXiv …, 2021 - arxiv.org
The heterogeneous edge-cloud computing paradigm can provide a more optimal direction
to deploy scientific workflows than traditional distributed computing or cloud computing …

Typetheoretic Approach to Big Data Workflow Composition

A Kashliev - 2024 IEEE 4th International Conference on …, 2024 - ieeexplore.ieee.org
Big data workflows have emerged as an important paradigm for analyzing increasingly large
datasets generated in different areas of human activity, including healthcare, climate …

A Performance Model for the Web Service Protocol Stacks

B Simon, B Goldschmidt… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Web services are built on XML. They use XML for describing the service interface, they use
XML for message exchange and the WS-* protocols that provide addressing, security and …

Deep Learning as Native Scientific Workflows in the Modern SWFMs-DATAVIEW

J Liu - 2022 - search.proquest.com
Scientific workflow has become a common practice for scientists to effectively formalize and
structure complex scientific processes, which in turn has accelerated scientific discoveries in …