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A control-based framework for self-managing distributed computing systems

Published: 31 October 2004 Publication History

Abstract

This paper describes an online control framework to design self-managing distributed computing systems that continually optimize their performance in response to changing computing demands and environmental conditions. An online control technique is used in conjunction with predictive filters to tune the performance of individual system components based on their forecast behavior. In a distributed setting, a global controller is used to manage the interaction between components such that overall system requirements are satisfied.

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    cover image ACM Conferences
    WOSS '04: Proceedings of the 1st ACM SIGSOFT workshop on Self-managed systems
    October 2004
    119 pages
    ISBN:1581139896
    DOI:10.1145/1075405
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 31 October 2004

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    WOSS04: Workshop on Self-Healing Systems [co-located with ACM SIGSOFT 2004 )
    October 31 - November 1, 2004
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    • (2023)Dynamic Resource Management for Cloud-native Bulk Synchronous Parallel Applications2023 IEEE 26th International Symposium on Real-Time Distributed Computing (ISORC)10.1109/ISORC58943.2023.00028(152-157)Online publication date: May-2023
    • (2021)Make your database system dream of electric sheepProceedings of the VLDB Endowment10.14778/3476311.347641114:12(3211-3221)Online publication date: 28-Oct-2021
    • (2019)Improving the energy efficiency of virtual data centers in an IT service provider through proactive fuzzy rules-based multicriteria decision makingThe Journal of Supercomputing10.1007/s11227-018-2301-175:3(1078-1093)Online publication date: 1-Mar-2019
    • (2018)Autonomic Data Streaming for High-Performance Scientific ApplicationsAutonomic Computing10.1201/9781315221564-32(437-458)Online publication date: 3-Oct-2018
    • (2016)Leveraging a predictive model of the workload for intelligent slot allocation schemes in energy-efficient HPC clustersEngineering Applications of Artificial Intelligence10.1016/j.engappai.2015.10.00348:C(95-105)Online publication date: 1-Feb-2016
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    • (2012)A High-Performance Cluster Management System Based on Distributed Hierarchical Autonomic Management MechanismProceedings of the 2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics - Volume 0110.1109/IHMSC.2012.81(297-300)Online publication date: 26-Aug-2012
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    • (2011)Software Maintenance through Supervisory ControlProceedings of the 2011 IEEE 34th Software Engineering Workshop10.1109/SEW.2011.20(97-105)Online publication date: 20-Jun-2011
    • (2011)Efficient Autoscaling in the Cloud Using Predictive Models for Workload ForecastingProceedings of the 2011 IEEE 4th International Conference on Cloud Computing10.1109/CLOUD.2011.42(500-507)Online publication date: 4-Jul-2011
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