scholarly journals Self-Adaptive Systems Planning with Model Checking using MAPE-K

2020 ◽  
Author(s):  
Aristóteles Esteves Marçal Da Silva ◽  
Aline Maria Santos Andrade ◽  
Sandro Santos Andrade
Keyword(s):  
Model Checking ◽  
Adaptive Systems ◽  
Traffic Monitoring ◽  
Self Healing ◽  
Reference Architecture ◽  
Systems Planning ◽  
Autonomous Planning ◽  
Formal Framework ◽  
Self Adaptive

This paper presents a model checking-based approach to support the autonomous planning of adaptation actions in Self-Adaptive Systems, designed in consonance with the MAPE-K reference architecture. We evaluated our approach with a case-study aiming at verifying self-healing and self-organizing properties in a distributed and decentralized traffic monitoring system. Results show that our approach is able to generate adaptation plans satisfying the goals for all expected scenarios in such a case-study, providing a flexible formal framework where adaptation strategies and goals can be inserted/removed.

scholarly journals PASTA: An Efficient Proactive Adaptation Approach Based on Statistical Model Checking for Self-Adaptive Systems

2021 ◽  
pp. 292-312
Author(s):  
Yong-Jun Shin ◽  
Eunho Cho ◽  
Doo-Hwan Bae
Keyword(s):  
Model Checking ◽  
Statistical Model ◽  
Adaptive Systems ◽  
Environmental Changes ◽  
Probabilistic Model Checking ◽  
Modeling Languages ◽  
Reference Architecture ◽  
Statistical Model Checking ◽  
Sas Model ◽  
Self Adaptive

AbstractProactive adaptation, in which the adaptation for a system’s reliable goal achievement is performed by predicting changes in the environment, is considered as an effective alternative to reactive adaptation, in which adaptation is performed after observing changes. When predicting the environmental changes, the prediction may be uncertain, so it is necessary to verify and confirm an adaptation’s consequences before execution. To resolve the uncertainty, probabilistic model checking (PMC) has been utilized for verification of adaptation tactics’ effects on the goal of a self-adaptive system (SAS). However, PMC-based approaches have limitations on the state-explosion problem of complex SAS model verification and the modeling languages supported by the model checkers. In this paper, to overcome the limitations of the PMC-based approaches, we propose an efficient Proactive Adaptation approach based on STAtistical model checking (PASTA). Our approach allows SASs to mitigate the uncertainty of the future environment, faster than the PMC-based approach, by producing statistically sufficient samples for verification of adaptation tactics based on statistical model checking (SMC) algorithms. We provide algorithmic processes, a reference architecture, and an open-source implementation skeleton of PASTA for engineers to apply it for SAS development. We evaluate PASTA on two SASs using actual data and show that PASTA is efficient comparing to the PMC-based approach. We also provide a comparative analysis of the advantages and disadvantages of PMC- and SMC-based proactive adaptation to guide engineers’ decision-making for SAS development.

Reliable Composition of MAPE-K Loops in Self-Adaptive Software Systems

2020 ◽  
Vol 10 (3) ◽  
pp. 38-54
Author(s):  
Selma Ouareth ◽  
Soufiane Boulehouache ◽  
Mazouzi Smaine
Keyword(s):  
Complex Systems ◽  
Knowledge Base ◽  
Electric Vehicle ◽  
Adaptive Systems ◽  
Design Approach ◽  
Software Systems ◽  
Adaptive Software ◽  
Control Loops ◽  
Self Adaptive

Self-adaptive systems (SASs) are controlled by autonomic manager (AM). This ensures the QoS of such complex systems within highly dynamic and unpredictable contexts. However, the massive integration of the adaptation abilities increased drastically the complexity of the AMs. To decrease the complexity and ensure correctness adaptation, scholars propose a subdivision into multi-autonomic entities (AEs) as a design approach. In such a design approach, SASs are controlled through multiple interacting AMs implementing each the well-known MAPE-K Loop. In this article, the writers propose a refinement pattern of interacting multiple MAPE-K Loops to achieve global adaptation without conflict. The authors contribute with a notation to describe the interaction of multiple MAPE-K Control Loops. To ensure the coordinated multi-attributes control, the interaction of the AEs is achieved through the knowledge base of the MAPE-K Loops. To validate the proposed pattern, a case study in the field of Electric Vehicle is presented.

scholarly journals Temporal Pattern Specifications for Self-Adaptive Requirements

2019 ◽  
Vol 12 (1) ◽  
pp. 58-68
Author(s):  
Ayoub Yahiaoui ◽  
Hakim Bendjenna ◽  
Philippe Roose ◽  
Lawrence Chung ◽  
Mohamed Amroune
Keyword(s):  
Assisted Living ◽  
Adaptive Systems ◽  
Smart Home ◽  
Ad Hoc ◽  
Ambient Assisted Living ◽  
Support Tool ◽  
Requirements Change ◽  
Self Adaptation ◽  
Self Adaptive

Background: Systems whose requirements change at a rate that necessitates adaptation without human intervention are called self-adaptive systems, and they have the ability to adjust their behavior autonomously at run-time in response to their environment’s evolution. Samples of applications that require self-adaptation include Smart home systems and environmental monitoring. However, self-adaptivity is often constructed in an ad-hoc manner. Methods: In this paper, the authors present a pattern-based specification language for self-adaptive systems. Its semantics are presented in terms of fuzzy logic. Thus, enabling a meticulous processing of requirements, in order to permit the formulation of self-adaptive requirements accurately, thereby facilitates the design of systems that are flexible and responsive to adaptation in a systematic manner. Results: To show the applicability and effectiveness of our language, the authors apply it to two case studies. One case study reviews the Smart fridge in ambient assisted living and the second case study is focused on an ambulance dispatching system using a developed support tool.

Sign in / Sign up

Export Citation Format

Share Document