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Full-Text Articles in Physical Sciences and Mathematics
Analyzing Latency-Aware Self-Adaptation Using Stochastic Games And Simulations, Javier Camara, Gabriel A. Moreno, David Garlan, Bradley Schmerl
Analyzing Latency-Aware Self-Adaptation Using Stochastic Games And Simulations, Javier Camara, Gabriel A. Moreno, David Garlan, Bradley Schmerl
Gabriel A. Moreno
Self-adaptive systems must decide which adaptations to apply and when. In reactive approaches, adaptations are chosen and executed after some issue in the system has been detected (e.g., unforeseen attacks or failures). In proactive approaches, predictions are used to prepare the system for some future event (e.g., traffic spikes during holidays). In both cases, the choice of adaptation is based on the estimated impact it will have on the system. Current decision-making approaches assume that the impact will be instantaneous, whereas it is common that adaptations take time to produce their impact. Ignoring this latency is problematic because adaptations may …
Proactive Self-Adaptation Under Uncertainty: A Probabilistic Model Checking Approach, Gabriel A. Moreno, Javier Camara, David Garlan, Bradley Schmerl
Proactive Self-Adaptation Under Uncertainty: A Probabilistic Model Checking Approach, Gabriel A. Moreno, Javier Camara, David Garlan, Bradley Schmerl
Gabriel A. Moreno
Self-adaptive systems tend to be reactive and myopic, adapting in response to changes without anticipating what the subsequent adaptation needs will be. Adapting reactively can result in inefficiencies due to the system performing a suboptimal sequence of adaptations. Furthermore, when adaptations have latency, and take some time to produce their effect, they have to be started with sufficient lead time so that they complete by the time their effect is needed. Proactive latency-aware adaptation addresses these issues by making adaptation decisions with a look-ahead horizon and taking adaptation latency into account. In this paper we present an approach for proactive …
Reasoning About Human Participation In Self-Adaptive Systems, Javier Camara, Gabriel A. Moreno, David Garlan
Reasoning About Human Participation In Self-Adaptive Systems, Javier Camara, Gabriel A. Moreno, David Garlan
Gabriel A. Moreno
Self-adaptive systems overcome many of the limitations of human supervision in complex software-intensive systems by endowing them with the ability to automatically adapt their structure and behavior in the presence of runtime changes. However, adaptation in some classes of systems (e.g., safety- critical) can benefit by receiving information from humans (e.g., acting as sophisticated sensors, decision-makers), or by involving them as system-level effectors to execute adaptations (e.g., when automation is not possible, or as a fallback mechanism). However, human participants are influenced by factors external to the system (e.g., training level, fatigue) that affect the likelihood of success when they …