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Flexible and Efficient Decision-Making for Proactive Latency-Aware Self-Adaptation

Authors:

Gabriel A. Moreno,

Javier Cámara,

Bradley SchmerlAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 13, Issue 1

Article No.: 3, Pages 1 - 36

https://doi.org/10.1145/3149180

Published: 16 April 2018 Publication History

Abstract

Proactive latency-aware adaptation is an approach for self-adaptive systems that considers both the current and anticipated adaptation needs when making adaptation decisions, taking into account the latency of the available adaptation tactics. Since this is a problem of selecting adaptation actions in the context of the probabilistic behavior of the environment, Markov decision processes (MDPs) are a suitable approach. However, given all the possible interactions between the different and possibly concurrent adaptation tactics, the system, and the environment, constructing the MDP is a complex task. Probabilistic model checking has been used to deal with this problem, but it requires constructing the MDP every time an adaptation decision is made to incorporate the latest predictions of the environment behavior. In this article, we describe PLA-SDP, an approach that eliminates that runtime overhead by constructing most of the MDP offline. At runtime, the adaptation decision is made by solving the MDP through stochastic dynamic programming, weaving in the environment model as the solution is computed. We also present extensions that support different notions of utility, such as maximizing reward gain subject to the satisfaction of a probabilistic constraint, making PLA-SDP applicable to systems with different kinds of adaptation goals.

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Cited By

Götz SBencomo NSamin HBaresi LMa XPasquale L(2024)Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data MirroringProceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3643915.3644106(182-188)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643915.3644106
Stevens CBagheri HRoychoudhury APaiva AAbreu RStorey M(2024)Scalable Relational Analysis via Relational Bound PropagationProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639171(1-12)Online publication date: 20-May-2024
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Xie SWang LLi QGuo X(2024)A Proactive Self-Adaptation Approach Based on Ensemble Prediction for Service-Based SystemsJournal of Circuits, Systems and Computers10.1142/S0218126624502347Online publication date: 14-Mar-2024
https://doi.org/10.1142/S0218126624502347
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Index Terms

Flexible and Efficient Decision-Making for Proactive Latency-Aware Self-Adaptation
1. Computing methodologies
  1. Artificial intelligence
    1. Planning and scheduling
      1. Planning under uncertainty
  2. Machine learning
    1. Machine learning approaches
      1. Markov decision processes

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Published In

cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 13, Issue 1

March 2018

184 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/3208359

Editor:
Bashar Nuseibeh
The Open University, UK

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Copyright © 2018 ACM.

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Publication History

Published: 16 April 2018

Accepted: 01 September 2017

Revised: 01 August 2017

Received: 01 February 2017

Published in TAAS Volume 13, Issue 1

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Carnegie Mellon University for the operation of the Software Engineering Institute

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Cited By

Götz SBencomo NSamin HBaresi LMa XPasquale L(2024)Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data MirroringProceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems10.1145/3643915.3644106(182-188)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1145/3643915.3644106
Stevens CBagheri HRoychoudhury APaiva AAbreu RStorey M(2024)Scalable Relational Analysis via Relational Bound PropagationProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639171(1-12)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639171
Xie SWang LLi QGuo X(2024)A Proactive Self-Adaptation Approach Based on Ensemble Prediction for Service-Based SystemsJournal of Circuits, Systems and Computers10.1142/S0218126624502347Online publication date: 14-Mar-2024
https://doi.org/10.1142/S0218126624502347
Aghili RQin QLi HKhomh F(2024)Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization2024 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58944.2024.00050(474-486)Online publication date: 6-Oct-2024
https://doi.org/10.1109/ICSME58944.2024.00050
Chen ZLi JLi NJiao W(2024)Reliable proactive adaptation via prediction fusion and extended stochastic model predictive controlJournal of Systems and Software10.1016/j.jss.2024.112166217:COnline publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.112166
Agos Jawaddi SIsmail AMohammad Hatta MKamarulzaman A(2024)Insights into cloud autoscaling: a unique perspective through MDP and DTMC formal modelsThe Journal of Supercomputing10.1007/s11227-023-05665-780:4(5073-5107)Online publication date: 1-Mar-2024
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Fang XYaman SCalinescu RWilson JPaterson C(2023)Predicting Nonfunctional Requirement Violations in Autonomous SystemsACM Transactions on Autonomous and Adaptive Systems10.1145/363240519:1(1-25)Online publication date: 14-Nov-2023
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Metzger AKley TRothweiler APohl K(2023)Automatically reconciling the trade-off between prediction accuracy and earliness in prescriptive business process monitoringInformation Systems10.1016/j.is.2023.102254118(102254)Online publication date: Sep-2023
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Matsutsuka TOgawa MToriyama YAso NIida I(2022)An Adaptive System for a Real-Time Matching ApplicationInternational Journal of Web Services Research10.4018/IJWSR.29901819:1(1-22)Online publication date: 15-Apr-2022
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