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HAFLoop: An archite...
HAFLoop: An architecture for supporting Highly Adaptive Feedback Loops in self-adaptive systems
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- Zavala, E. (författare)
- Universitat Politecnica de Catalunya,Polytechnic University of Catalonia
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- Franch, X. (författare)
- Universitat Politecnica de Catalunya,Polytechnic University of Catalonia
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- Marco, J. (författare)
- Universitat Politecnica de Catalunya,Polytechnic University of Catalonia
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- Berger, Christian, 1980 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),University of Gothenburg
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(creator_code:org_t)
- Elsevier BV, 2020
- 2020
- Engelska.
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Ingår i: Future Generation Computer Systems-the International Journal of Escience. - : Elsevier BV. - 0167-739X. ; 105:April, s. 607-630
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Inbäddad systemteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Embedded Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Self-adaptive system
- Smart vehicle
- IoT system
- Adaptive monitoring
- Adaptive feedback loop
- Self-improvement
- adaptation
- driven
- Computer Science
- IoT system
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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