TY - GEN
T1 - Knowledge aggregation with subjective logic in multi-agent self-adaptive cyber-physical systems
AU - Petrovska, Ana
AU - Quijano, Sergio
AU - Gerostathopoulos, Ilias
AU - Pretschner, Alexander
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/6/29
Y1 - 2020/6/29
N2 - Modern software systems, such as cyber-physical systems (CPSs), operate in complex and dynamic environments. With the continuous and unanticipated change in the operational environment, these systems are subjected to a variety of uncertainties. Self-adaptive CPSs (SACPSs) can adjust their behavior or structure at run-time as a response to the changes in their perceived environment. Namely, self-adaptation is commonly realized through a MAPE-K feedback loop incorporating newly derived knowledge obtained by the sensed data from the run-time monitoring, during the operation of decentralized SACPSs. However, to build the knowledge, the need for run-time observations' aggregation and reasoning emerges, since the observations made by the decentralized systems might be conflicting. In this paper, we propose an approach for observations aggregation and knowledge modeling in SACPSs that is domain-independent and can deal with inaccurate, partial, and conflicting observations, based on the formalisms of Subjective Logic.
AB - Modern software systems, such as cyber-physical systems (CPSs), operate in complex and dynamic environments. With the continuous and unanticipated change in the operational environment, these systems are subjected to a variety of uncertainties. Self-adaptive CPSs (SACPSs) can adjust their behavior or structure at run-time as a response to the changes in their perceived environment. Namely, self-adaptation is commonly realized through a MAPE-K feedback loop incorporating newly derived knowledge obtained by the sensed data from the run-time monitoring, during the operation of decentralized SACPSs. However, to build the knowledge, the need for run-time observations' aggregation and reasoning emerges, since the observations made by the decentralized systems might be conflicting. In this paper, we propose an approach for observations aggregation and knowledge modeling in SACPSs that is domain-independent and can deal with inaccurate, partial, and conflicting observations, based on the formalisms of Subjective Logic.
KW - cyber-physical systems
KW - knowledge aggregation
KW - reasoning
KW - self-adaptive systems
KW - subjective logic
UR - http://www.scopus.com/inward/record.url?scp=85093122120&partnerID=8YFLogxK
U2 - 10.1145/3387939.3391600
DO - 10.1145/3387939.3391600
M3 - Conference contribution
AN - SCOPUS:85093122120
T3 - Proceedings - 2020 IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2020
SP - 149
EP - 155
BT - Proceedings - 2020 IEEE/ACM 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2020
PB - Association for Computing Machinery, Inc
T2 - 15th IEEE/ACM International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2020
Y2 - 29 June 2020 through 3 July 2020
ER -