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An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems

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Title: An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems
Authors: Jamshidi, P
Casale, G
Item Type: Conference Paper
Abstract: Finding optimal configurations for Stream Processing Systems (SPS) is a challenging problem due to the large number of parameters that can influence their performance and the lack of analytical models to anticipate the effect of a change. To tackle this issue, we consider tuning methods where an experimenter is given a limited budget of experiments and needs to carefully allocate this budget to find optimal configurations. We propose in this setting Bayesian Optimization for Configuration Optimization (BO4CO), an auto-tuning algorithm that leverages Gaussian Processes (GPs) to iteratively capture posterior distributions of the configuration spaces and sequentially drive the experimentation. Validation based on Apache Storm demonstrates that our approach locates optimal configurations within a limited experimental budget, with an improvement of SPS performance typically of at least an order of magnitude compared to existing configuration algorithms.
Issue Date: 8-Dec-2016
Date of Acceptance: 17-Jun-2016
URI: http://hdl.handle.net/10044/1/33790
DOI: https://dx.doi.org/10.1109/MASCOTS.2016.17
ISSN: 2375-0227
Publisher: IEEE
Journal / Book Title: 2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)
Copyright Statement: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 644869
Conference Name: IEEE MASCOTS
Keywords: Science & Technology
Engineering, Electrical & Electronic
Publication Status: Published
Start Date: 2016-09-19
Finish Date: 2016-09-21
Conference Place: London, UK
Appears in Collections:Computing
Faculty of Engineering