Tuning self-adaptation in cyber-physical systems through architectural homeostasis

被引:18
作者
Gerostathopoulos, Ilias [1 ]
Skoda, Dominik [2 ]
Plasil, Frantisek [2 ]
Bures, Tomas [2 ]
Knauss, Alessia [3 ]
机构
[1] Tech Univ Munich, Fak Informat, Munich, Germany
[2] Charles Univ Prague, Fac Math & Phys, Prague, Czech Republic
[3] Chalmers Univ Technol, Dept Comp Sci & Engn, Gothenburg, Sweden
关键词
Cyber-physical systems; Software architecture; Run-time uncertainty; Self-adaptation strategies; Architecture homeostasis; MODELS;
D O I
10.1016/j.jss.2018.10.051
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Self-adaptive software-intensive cyber-physical systems (sasiCPS) encounter a high level of run-time uncertainty. State-of-the-art architecture-based self-adaptation approaches assume designing against a fixed set of situations that warrant self-adaptation. As a result, failures may appear when sasiCPS operate in environment conditions they are not specifically designed for. In response, we propose to increase the homeostasis of sasiCPS, i.e., the capacity to maintain an operational state despite run-time uncertainty, by introducing run-time changes to the architecture-based self-adaptation strategies according to environment stimuli. In addition to articulating the main idea of architectural homeostasis, we introduce four mechanisms that reify the idea: (i) collaborative sensing, (ii) faulty component isolation from adaptation, (iii) enhancing mode switching, and (iv) adjusting guards in mode switching. Moreover, our experimental evaluation of the four mechanisms in two different case studies confirms that allowing a complex system to change its self-adaptation strategies helps the system recover from run-time errors and abnormalities and keep it in an operational state. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:37 / 55
页数:19
相关论文
共 48 条
[1]  
[Anonymous], 2005, PRACTICAL MATH OPTIM
[2]  
[Anonymous], 2011, SIGSOFT FSE 11 19 AC, DOI DOI 10.1145/2025113.2025147
[3]  
Baresi L., 2010, Proceedings of the 2010 IEEE 18th International Conference on Requirements Engineering (RE2010), P125, DOI 10.1109/RE.2010.25
[4]  
Beetz K., 2012, Model-Based Engineering of Embedded Systems, P3
[5]  
Braberman Victor, 2015, INT WS CONTROL THEOR, P9
[6]   Engineering Self-Adaptive Systems through Feedback Loops [J].
Brun, Yuriy ;
Serugendo, Giovanna Di Marzo ;
Gacek, Cristina ;
Giese, Holger ;
Kienle, Holger ;
Litoiu, Marin ;
Mueller, Hausi ;
Pezze, Mauro ;
Shaw, Mary .
SOFTWARE ENGINEERING FOR SELF-ADAPTIVE SYSTEMS, 2009, 5525 :48-+
[7]  
Bures T., 2013, CBSE 2013, P81, DOI DOI 10.1145/2465449.2465462
[8]   Software Abstractions for Component Interaction in the Internet of Things [J].
Bures, Tomas ;
Plasil, Frantisek ;
Kit, Michal ;
Tuma, Petr ;
Hoch, Nicklas .
COMPUTER, 2016, 49 (12) :50-59
[9]  
Cheng B. H. C., 2009, P IEEE C SENS MESH A, P1, DOI [DOI 10.1145/1640206.1640216, DOI 10.1007/978-3-642-04425-0_36]
[10]   Software Engineering for Self-Adaptive Systems: A Research Roadmap [J].
Cheng, Betty H. C. ;
de Lemos, Rogerio ;
Giese, Holger ;
Inverardi, Paola ;
Magee, Jeff ;
Andersson, Jesper ;
Becker, Basil ;
Bencomo, Nelly ;
Brun, Yuriy ;
Cukic, Bojan ;
Serugendo, Giovanna Di Marzo ;
Dustdar, Schahram ;
Finkelstein, Anthony ;
Gacek, Cristina ;
Geihs, Kurt ;
Grassi, Vincenzo ;
Karsai, Gabor ;
Kienle, Holger M. ;
Kramer, Jeff ;
Litoiu, Marin ;
Malek, Sam ;
Mirandola, Raffaela ;
Mueller, Hausi A. ;
Park, Sooyong ;
Shaw, Mary ;
Tichy, Matthias ;
Tivoli, Massimo ;
Weyns, Danny ;
Whittle, Jon .
SOFTWARE ENGINEERING FOR SELF-ADAPTIVE SYSTEMS, 2009, 5525 :1-+