As Grid Computing increasingly enters the commercial domain, performance and Quality of Service (QoS) issues are becoming a major concern. The inherent complexity, heterogeneity and dynamics of Grid computing environments pose some challenges in managing their capacity to ensure that QoS requirements are continuously met. In this paper, a comprehensive framework for autonomic QoS control in enterprise Grid environments using online simulation is proposed. The paper presents a novel methodology for designing autonomic QoS-aware resource managers that have the capability to predict the performance of the Grid components they manage and allocate resources in such a way that service level agreements are honored. Support for advanced features such as autonomic workload characterization on-the-fly, dynamic deployment of Grid servers on demand, as well as dynamic system reconfiguration after a server failure is provided. The goal is to make the Grid middleware self-configurable and adaptable to changes in the system environment and workload. The approach is subjected to an extensive experimental evaluation in the context of a real-world Grid environment and its effectiveness, practicality and performance are demonstrated.
%0 Journal Article
%1 NoKoJuTo2008-JSS-GridAutoQoS
%A Nou, Ramon
%A Kounev, Samuel
%A Julia, Ferran
%A Torres, Jordi
%C Amsterdam, The Netherlands
%D 2009
%I Elsevier Science Publishers B. V.
%J Journal of Systems and Software
%K Analytical_and_simulation-based_analysis Application_quality_of_service_management Automated_model_learning Design_of_software_and_systems Formal_architecture_modeling Grid Instrumentation_profiling_and_workload_characterization Performance Prediction QPME_Bibliography QPN Reliability Resource_management SOA Self-adaptive-systems Self-aware-computing Simulation descartes t_journalmagazine
%N 3
%P 486--502
%T Autonomic QoS control in enterprise Grid environments using online simulation
%V 82
%X As Grid Computing increasingly enters the commercial domain, performance and Quality of Service (QoS) issues are becoming a major concern. The inherent complexity, heterogeneity and dynamics of Grid computing environments pose some challenges in managing their capacity to ensure that QoS requirements are continuously met. In this paper, a comprehensive framework for autonomic QoS control in enterprise Grid environments using online simulation is proposed. The paper presents a novel methodology for designing autonomic QoS-aware resource managers that have the capability to predict the performance of the Grid components they manage and allocate resources in such a way that service level agreements are honored. Support for advanced features such as autonomic workload characterization on-the-fly, dynamic deployment of Grid servers on demand, as well as dynamic system reconfiguration after a server failure is provided. The goal is to make the Grid middleware self-configurable and adaptable to changes in the system environment and workload. The approach is subjected to an extensive experimental evaluation in the context of a real-world Grid environment and its effectiveness, practicality and performance are demonstrated.
@article{NoKoJuTo2008-JSS-GridAutoQoS,
abstract = {As Grid Computing increasingly enters the commercial domain, performance and Quality of Service (QoS) issues are becoming a major concern. The inherent complexity, heterogeneity and dynamics of Grid computing environments pose some challenges in managing their capacity to ensure that QoS requirements are continuously met. In this paper, a comprehensive framework for autonomic QoS control in enterprise Grid environments using online simulation is proposed. The paper presents a novel methodology for designing autonomic QoS-aware resource managers that have the capability to predict the performance of the Grid components they manage and allocate resources in such a way that service level agreements are honored. Support for advanced features such as autonomic workload characterization on-the-fly, dynamic deployment of Grid servers on demand, as well as dynamic system reconfiguration after a server failure is provided. The goal is to make the Grid middleware self-configurable and adaptable to changes in the system environment and workload. The approach is subjected to an extensive experimental evaluation in the context of a real-world Grid environment and its effectiveness, practicality and performance are demonstrated.},
added-at = {2020-04-06T11:21:31.000+0200},
address = {Amsterdam, The Netherlands},
author = {Nou, Ramon and Kounev, Samuel and Julia, Ferran and Torres, Jordi},
biburl = {https://www.bibsonomy.org/bibtex/25c5b2c42b0101f1416682a2d9754ca4c/se-group},
interhash = {1ff3e7ee476693b3a5572832e1f445d6},
intrahash = {5c5b2c42b0101f1416682a2d9754ca4c},
journal = {Journal of Systems and Software},
keywords = {Analytical_and_simulation-based_analysis Application_quality_of_service_management Automated_model_learning Design_of_software_and_systems Formal_architecture_modeling Grid Instrumentation_profiling_and_workload_characterization Performance Prediction QPME_Bibliography QPN Reliability Resource_management SOA Self-adaptive-systems Self-aware-computing Simulation descartes t_journalmagazine},
month = {March},
number = 3,
pages = {486--502},
publisher = {Elsevier Science Publishers B. V.},
timestamp = {2021-08-17T12:45:13.000+0200},
title = {{Autonomic QoS control in enterprise Grid environments using online simulation}},
volume = 82,
year = 2009
}