Abstract
AbstractArchitecting a self-adaptive system with decentralized control is challenging. Indeed, architects shall consider several different and interdependent design dimensions and devise multiple control loops to coordinate and timely perform the correct adaptations. To support this task, we propose Decor, a reasoning framework for architecting and evaluating decentralized control. Decor provides (i) multi-paradigm modeling support, (ii) a modeling environment for MAPE-K style decentralized control, and (iii) a co-simulation environment for simulating the decentralized control together with the managed system and estimating the quality attributes of interest. We apply the Decor in three case studies: an intelligent transportation system, a smart power grid, and a cloud computing application. The studies demonstrate the framework’s capabilities to support informed architectural decisions on decentralized control and adaptation strategies.
Publisher
Springer Science and Business Media LLC
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software
Reference62 articles.
1. Abbas N, Andersson J (2013) Architectural reasoning for dynamic software product lines. In: Proceedings of the 17th International Software Product Line Conference Co-Located Workshops
2. Abbas N, Andersson J, Weyns D (2020) Asple: A methodology to develop self-adaptive software systems with systematic reuse. J Syst Softw 167
3. Arcaini P, Riccobene E, Scandurra P (2017) Formal design and verification of self-adaptive systems with decentralized control. ACM Trans Auton Adapt Syst 11(4)
4. Bass L, Clements P, Kazman R (2003) Software Architecture in Practice. Addison-Wesley
5. Bass L, Clements P, Kazman R (2012) Software Architecture in Practice, 3rd edn. Addison-Wesley Professional, Boston
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Networked control systems and their applications to smart satellites: a survey;Sensors and Systems for Space Applications XVII;2024-06-06
2. Self-Adaptive Large Language Model (LLM)-Based Multiagent Systems;2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C);2023-09-25