TY - GEN
T1 - Architectural homeostasis in self-adaptive software-intensive cyber-physical systems
AU - Gerostathopoulos, Ilias
AU - Skoda, Dominik
AU - Plasil, Frantisek
AU - Bures, Tomas
AU - Knauss, Alessia
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Self-adaptive software-intensive cyber-physical systems (sasiCPS) encounter a high level of run-time uncertainty. State-of-the-art architecturebased 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 describe three mechanisms that reify the idea: (i) collaborative sensing, (ii) faulty component isolation from adaptation, and (iii) enhancing mode switching. Moreover, our experimental evaluation of the three mechanisms confirms that allowing a complex system to change its self-adaptation strategies helps the system recover from runtime errors and abnormalities and keep it in an operational state.
AB - Self-adaptive software-intensive cyber-physical systems (sasiCPS) encounter a high level of run-time uncertainty. State-of-the-art architecturebased 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 describe three mechanisms that reify the idea: (i) collaborative sensing, (ii) faulty component isolation from adaptation, and (iii) enhancing mode switching. Moreover, our experimental evaluation of the three mechanisms confirms that allowing a complex system to change its self-adaptation strategies helps the system recover from runtime errors and abnormalities and keep it in an operational state.
KW - Cyber-physical systems
KW - Run-time uncertainty
KW - Self-adaptation strategies
KW - Software architecture
UR - http://www.scopus.com/inward/record.url?scp=84998893291&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84998893291&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-48992-6_8
DO - 10.1007/978-3-319-48992-6_8
M3 - Conference contribution
AN - SCOPUS:84998893291
SN - 9783319489919
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 113
EP - 128
BT - Software Architecture - 10th European Conference, ECSA 2016, Proceedings
A2 - Babar, Ali
A2 - Zdun, Uwe
A2 - Tekinerdogan, Bedir
PB - Springer Verlag
T2 - 10th European Conference on Software Architecture, ECSA 2016
Y2 - 28 November 2016 through 2 December 2016
ER -