Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.
Original languageUnknown
Title of host publicationIEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC)
Pages423-430
DOIs
Publication statusPublished - 1 Jan 2012
EventUbiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on -
Duration: 1 Jan 2012 → …

Conference

ConferenceUbiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on
Period1/01/12 → …

Cite this

Cunha, J. A. C. E. (2012). Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework. In IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC) (pp. 423-430) https://doi.org/10.1109/UIC-ATC.2012.14
Cunha, José Alberto Cardoso E. / Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework. IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC). 2012. pp. 423-430
@inproceedings{c9aa41ccc03741f0a898a326b8468935,
title = "Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework",
abstract = "Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.",
author = "Cunha, {Jos{\'e} Alberto Cardoso E}",
year = "2012",
month = "1",
day = "1",
doi = "10.1109/UIC-ATC.2012.14",
language = "Unknown",
isbn = "978-1-4673-3084-8",
pages = "423--430",
booktitle = "IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC)",

}

Cunha, JACE 2012, Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework. in IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC). pp. 423-430, Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on, 1/01/12. https://doi.org/10.1109/UIC-ATC.2012.14

Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework. / Cunha, José Alberto Cardoso E.

IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC). 2012. p. 423-430.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework

AU - Cunha, José Alberto Cardoso E

PY - 2012/1/1

Y1 - 2012/1/1

N2 - Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.

AB - Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.

U2 - 10.1109/UIC-ATC.2012.14

DO - 10.1109/UIC-ATC.2012.14

M3 - Conference contribution

SN - 978-1-4673-3084-8

SP - 423

EP - 430

BT - IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC)

ER -

Cunha JACE. Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework. In IEEE 9th International Conference on Ubiquitous Intelligence and Computing (UIC) / IEEE 9th International Conference on Autonomic and Trusted Computing (ATC). 2012. p. 423-430 https://doi.org/10.1109/UIC-ATC.2012.14