RDMSim:An Exemplar for Evaluation and Comparison of Decision-Making Techniques for Self-Adaptation

Abstract

Decision-making for self-adaptation approaches need to address different challenges, including the quantification of the uncertainty of events that cannot be foreseen in advance and their effects, and dealing with conflicting objectives that inherently involve multi-objective decision making (e.g., avoiding costs vs. providing reliable service). To enable researchers to evaluate and compare decision-making techniques for self-adaptation, we present the RDMSim exemplar. RDMSim enables researchers to evaluate and compare techniques for decision-making under environmental uncertainty that support self-adaptation. The focus of the exemplar is on the domain problem related to Remote Data Mirroring, which gives opportunity to face the challenges described above. RDMSim provides probe and effector components for easy integration with external adaptation managers, which are associated with decision-making techniques and based on the MAPE-K loop. Specifically, the paper presents (i) RDMSim, a simulator for real-world experimentation, (ii) a set of realistic simulation scenarios that can be used for experimentation and comparison purposes, (iii) data for the sake of comparison.

Publication DOI: https://doi.org/10.1109/SEAMS51251.2021.00039
Divisions: College of Engineering & Physical Sciences > Computer Science
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: © 2021 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. Funding: This work has been partially supported by The Leverhulme Trust Fellowship ”QuantUn: quantification of uncertainty using Bayesian surprises” (Grant No. RF-2019-548/9) and the EPSRC Research Project Twenty20Insight (Grant No. EP/T017627/1).
Event Title: 2021 International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
Event Type: Other
Event Location: Madrid, Spain
Event Dates: 2021-05-18 - 2021-05-24
Uncontrolled Keywords: Exemplar,Remote Data Mirroring,Self-Adaptive System,Computer Science Applications,Artificial Intelligence,Control and Optimization,Software,Information Systems and Management,Industrial and Manufacturing Engineering
ISBN: 978-1-6654-0290-3, 978-1-6654-0289-7
Full Text Link:
Related URLs: https://ieeexpl ... cument/9462042/ (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2021-06-29
Accepted Date: 2021-03-12
Authors: Samin, Huma
Paucar, Luis H. Garcia (ORCID Profile 0000-0003-2915-0830)
Bencomo, Nelly (ORCID Profile 0000-0001-6895-1636)
Hurtado, Cesar M. Carranza
Fredericks, Erik M.

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