research-article

Applying genetic algorithms to decision making in autonomic computing systems

Authors:

Andres J. Ramirez,

David B. Knoester,

Betty H.C. Cheng,

Philip K. McKinleyAuthors Info & Claims

ICAC '09: Proceedings of the 6th international conference on Autonomic computing

Pages 97 - 106

https://doi.org/10.1145/1555228.1555258

Published: 15 June 2009 Publication History

Abstract

Increasingly, applications need to be able to self-reconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means for automating software maintenance tasks. As the complexity of adaptive and autonomic systems grows, designing and managing the set of reconfiguration rules becomes increasingly challenging and may produce inconsistencies. This paper proposes an approach to leverage genetic algorithms in the decision-making process of an autonomic system. This approach enables a system to dynamically evolve reconfiguration plans at run time in response to changing requirements and environmental conditions. A key feature of this approach is incorporating system and environmental monitoring information into the genetic algorithm such that specific changes in the environment automatically drive the evolutionary process towards new viable solutions. We have applied this genetic-algorithm based approach to the dynamic reconfiguration of a collection of remote data mirrors, with the goal of minimizing costs while maximizing data reliability and network performance, even in the presence of link failures.

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Jamil MNour MAlotaibi SHussain MHussaini SNaseer A(2023)Adaptive Test Suits Generation for Self-Adaptive Systems Using SPEA2 AlgorithmApplied Sciences10.3390/app13201132413:20(11324)Online publication date: 15-Oct-2023
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Index Terms

Applying genetic algorithms to decision making in autonomic computing systems
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Dynamic programming

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Published In

cover image ACM Conferences

ICAC '09: Proceedings of the 6th international conference on Autonomic computing

June 2009

198 pages

ISBN:9781605585642

DOI:10.1145/1555228

General Chairs:
Simon Dobson
UCD Dublin, IE
,
John Strassner
Waterford Institute of Technology, IE
,
Program Chairs:
Manish Parashar
Rutgers University, USA
,
Onn Shehory
IBM Research Haifa, IL

Copyright © 2009 ACM.

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Published: 15 June 2009

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ICAC '09: 6th International Conference on Autonomic Computing

June 15 - 19, 2009

Barcelona, Spain

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Cited By

Chen PChen TLi M(2024)MMO: Meta Multi-Objectivization for Software Configuration TuningIEEE Transactions on Software Engineering10.1109/TSE.2024.338891050:6(1478-1504)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3388910
Da Silva AKnissel TWeiss G(2024)Self-Adaptive Optimization Techniques for Matrix Production Systems2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)10.1109/CASE59546.2024.10711799(1163-1168)Online publication date: 28-Aug-2024
https://doi.org/10.1109/CASE59546.2024.10711799
Jamil MNour MAlotaibi SHussain MHussaini SNaseer A(2023)Adaptive Test Suits Generation for Self-Adaptive Systems Using SPEA2 AlgorithmApplied Sciences10.3390/app13201132413:20(11324)Online publication date: 15-Oct-2023
https://doi.org/10.3390/app132011324
Chen TLi M(2023)The Weights Can Be Harmful: Pareto Search versus Weighted Search in Multi-objective Search-based Software EngineeringACM Transactions on Software Engineering and Methodology10.1145/351423332:1(1-40)Online publication date: 13-Feb-2023
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Yatsenko AWolff CParkhomenko ATulenkov A(2023)Methods and Tools for Minimizing the Power Consumption of Wireless Sensor Network2023 IEEE European Technology and Engineering Management Summit (E-TEMS)10.1109/E-TEMS57541.2023.10424609(122-127)Online publication date: 20-Apr-2023
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Chen TLi M(2022)Do Performance Aspirations Matter for Guiding Software Configuration Tuning? An Empirical Investigation under Dual Performance ObjectivesACM Transactions on Software Engineering and Methodology10.1145/357185332:3(1-41)Online publication date: 24-Nov-2022
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Weyns DGheibi OQuin FVan Der Donckt J(2022)Deep Learning for Effective and Efficient Reduction of Large Adaptation Spaces in Self-adaptive SystemsACM Transactions on Autonomous and Adaptive Systems10.1145/353019217:1-2(1-42)Online publication date: 29-Jul-2022
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