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Akiki, Paul A.
(2021).
DOI: https://doi.org/10.1145/3468264.3473098
Abstract
Resource-driven systems have tasks that are bound by limited resources. These systems must adapt their tasks that cannot gain access to sufficient resources. This dissertation proposes a new resource-driven adaptation approach, which aims to support (1) task prioritisation using multiple criteria such as the time of day that a task should be executed, the role of involved users, and selection of the least costly adaptation types; (2) collaboration between a human user and a software tool for preparing adapted task behaviour to be used when resources are substituted; and (3) resource extensibility and heterogeneity. The proposed approach is being implemented and will be evaluated with scenarios from enterprise applications.