research-article

A multi-model framework to implement self-managing control systems for QoS management

Authors:

Tharindu Patikirikorala,

Liuping WangAuthors Info & Claims

SEAMS '11: Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Pages 218 - 227

https://doi.org/10.1145/1988008.1988040

Published: 23 May 2011 Publication History

Abstract

Many control theory based approaches have been proposed to provide QoS assurance in increasingly complex software systems. These approaches generally use single model based, fixed or adaptive control techniques for QoS management of such systems. With varying system dynamics and unpredictable environmental changes, however, it is difficult to design a single model or controller to achieve the desired QoS performance across all the operating regions of these systems. In this paper, we propose a multi-model framework to capture the multi-model nature of software systems and implement self-managing control systems for them. A reference-model and extendable class library are introduced to implement such self-managing control systems. The proposed approach is also validated and compared to fixed and adaptive control schemes through a range of experiments.

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Cited By

Barakabitze AMkwawa IHines AWalshe R(2023)QoE-Aware Dynamic Resource Management in Future Softwarized and Virtualized NetworksIEEE Access10.1109/ACCESS.2023.330959911(93310-93330)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3309599
Lipitakis AKousiouris GNikolaidou MBardaki CAnagnostopoulos D(2023)Empirical investigation of factors influencing function as a service performance in different cloud/edge system setupsSimulation Modelling Practice and Theory10.1016/j.simpat.2023.102808128(102808)Online publication date: Nov-2023
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Index Terms

A multi-model framework to implement self-managing control systems for QoS management
1. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods

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cover image ACM Conferences

SEAMS '11: Proceedings of the 6th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

May 2011

246 pages

ISBN:9781450305754

DOI:10.1145/1988008

Program Chairs:
Holger Giese
Hasso Plattner Institute, Germany
,
Betty H.C. Cheng
Michigan State University, USA

Copyright © 2011 ACM.

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Published: 23 May 2011

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ICSE11: International Conference on Software Engineering

May 23 - 24, 2011

HI, Waikiki, Honolulu, USA

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Overall Acceptance Rate 17 of 31 submissions, 55%

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Cited By

Barakabitze AMkwawa IHines AWalshe R(2023)QoE-Aware Dynamic Resource Management in Future Softwarized and Virtualized NetworksIEEE Access10.1109/ACCESS.2023.330959911(93310-93330)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3309599
Lipitakis AKousiouris GNikolaidou MBardaki CAnagnostopoulos D(2023)Empirical investigation of factors influencing function as a service performance in different cloud/edge system setupsSimulation Modelling Practice and Theory10.1016/j.simpat.2023.102808128(102808)Online publication date: Nov-2023
https://doi.org/10.1016/j.simpat.2023.102808
Niranjan YNarayana MVijaya Sudha M(2023)Virtual Machine Migration Framework with Configuration Change ManagementInnovations in Computer Science and Engineering10.1007/978-981-19-7455-7_49(633-644)Online publication date: 4-May-2023
https://doi.org/10.1007/978-981-19-7455-7_49
Cai ZBuyya R(2022)Inverse Queuing Model-Based Feedback Control for Elastic Container Provisioning of Web Systems in KubernetesIEEE Transactions on Computers10.1109/TC.2021.304959871:2(337-348)Online publication date: 1-Feb-2022
https://doi.org/10.1109/TC.2021.3049598
Salama MBahsoon RLago P(2021)Stability in Software Engineering: Survey of the State-of-the-Art and Research DirectionsIEEE Transactions on Software Engineering10.1109/TSE.2019.292561647:7(1468-1510)Online publication date: 1-Jul-2021
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Sacco AFlocco MEsposito FMarchetto G(2021)Supporting Sustainable Virtual Network Mutations With MystiqueIEEE Transactions on Network and Service Management10.1109/TNSM.2021.305964718:3(2714-2727)Online publication date: Sep-2021
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Cai ZLiu DLu YBuyya R(2020)Unequal‐interval based loosely coupled control method for auto‐scaling heterogeneous cloud resources for web applicationsConcurrency and Computation: Practice and Experience10.1002/cpe.592632:23Online publication date: 8-Jul-2020
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Barna CLitoiu MFokaefs MShtern MWigglesworth JWolter KKnottenbelt Wvan Hoorn ANambiar MKoziolek H(2018)Runtime Performance Management for Cloud Applications with Adaptive ControllersProceedings of the 2018 ACM/SPEC International Conference on Performance Engineering10.1145/3184407.3184438(176-183)Online publication date: 30-Mar-2018
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Qu CCalheiros RBuyya R(2018)Auto-Scaling Web Applications in CloudsACM Computing Surveys10.1145/314814951:4(1-33)Online publication date: 13-Jul-2018
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