TY - GEN
T1 - Run-Time Adaptation of Quality Attributes for Automated Planning
AU - Wohlrab, Rebekka
AU - Meira-Goes, Romulo
AU - Vierhauser, Michael
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022
Y1 - 2022
N2 - Self-Adaptive systems typically operate in heterogeneous environments and need to optimize their behavior based on a variety of quality attributes to meet stakeholders' needs. During adaptation planning, these quality attributes are considered in the form of constraints, describing requirements that must be fulfilled, and utility functions, which are used to select an optimal plan among several alternatives. Up until now, most automated planning approaches are not designed to adapt quality attributes, their priorities, and their trade-offs at run time. Instead, both utility functions and constraints are commonly defined at design time. There exists a clear lack of run-Time mechanisms that support their adaptation in response to changes in the environment or in stakeholders' preferences. In this paper, we present initial work that combines automated planning and adaptation of quality attributes to address this gap. The approach helps to semi-Automatically adjust utility functions and constraints based on changes at run time. We present a preliminary experimental evaluation that indicates that our approach can provide plans with higher utility values while fulfilling changed or added constraints. We conclude this paper with our envisioned research outlook and plans for future empirical studies.
AB - Self-Adaptive systems typically operate in heterogeneous environments and need to optimize their behavior based on a variety of quality attributes to meet stakeholders' needs. During adaptation planning, these quality attributes are considered in the form of constraints, describing requirements that must be fulfilled, and utility functions, which are used to select an optimal plan among several alternatives. Up until now, most automated planning approaches are not designed to adapt quality attributes, their priorities, and their trade-offs at run time. Instead, both utility functions and constraints are commonly defined at design time. There exists a clear lack of run-Time mechanisms that support their adaptation in response to changes in the environment or in stakeholders' preferences. In this paper, we present initial work that combines automated planning and adaptation of quality attributes to address this gap. The approach helps to semi-Automatically adjust utility functions and constraints based on changes at run time. We present a preliminary experimental evaluation that indicates that our approach can provide plans with higher utility values while fulfilling changed or added constraints. We conclude this paper with our envisioned research outlook and plans for future empirical studies.
UR - http://www.scopus.com/inward/record.url?scp=85134155194&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134155194&partnerID=8YFLogxK
U2 - 10.1145/3524844.3528063
DO - 10.1145/3524844.3528063
M3 - Conference contribution
AN - SCOPUS:85134155194
T3 - Proceedings - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
SP - 98
EP - 105
BT - Proceedings - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2022
Y2 - 18 May 2022 through 20 May 2022
ER -