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HAFLoop: An architecture for supporting Highly Adaptive Feedback Loops in self-adaptive systems

Artikel i vetenskaplig tidskrift
Författare E. Zavala
X. Franch
J. Marco
Christian Berger
Publicerad i Future Generation Computer Systems-the International Journal of Escience
Volym 105
Nummer/häfte April
Sidor 607-630
ISSN 0167-739X
Publiceringsår 2020
Publicerad vid Institutionen för data- och informationsteknik (GU)
Sidor 607-630
Språk en
Länkar dx.doi.org/10.1016/j.future.2019.12...
Ämnesord Self-adaptive system, Smart vehicle, IoT system, Adaptive monitoring, Adaptive feedback loop, Self-improvement, adaptation, driven, Computer Science
Ämneskategorier Data- och informationsvetenskap

Sammanfattning

Most of the current self-adaptive systems (SASs) rely on static feedback loops such as the IBM's MAPEK loop for managing their adaptation process. Static loops do not allow SASs to react to runtime events such as changing adaptation requirements or MAPE-K elements' faults. In order to address this issue, some solutions have emerged for manually or automatically perform changes on SASs' feedback loops. However, from the software engineering perspective, most of the proposals cannot be reused or extended by other SASs. In this paper, we present HAFLoop (Highly Adaptive Feedback control Loop), a generic architectural proposal that aims at easing and fastening the design and implementation of adaptive feedback loops in modern SASs. Our solution enables both structural and parameter adaptation of the loop elements. Moreover, it provides a highly modular design that allows SASs' owners to support a variety of feedback loop settings from centralized to fully decentralized. In this work, HAFLoop has been implemented as a framework for Java-based systems and evaluated in two emerging software application domains: self-driving vehicles and IoT networks. Results demonstrate that our proposal easies and accelerates the development of adaptive feedback loops as well as how it could help to address some of the most relevant challenges of self-driving vehicles and IoT applications. Concretely, HAFLoop has demonstrated to improve SASs' feedback loops' runtime availability and operation. (C) 2019 Elsevier B.V. All rights reserved.

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