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Selected Works

Self-adaptation

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Articles 1 - 7 of 7

Full-Text Articles in Physical Sciences and Mathematics

Architecture-Based Self-Adaptation For Moving Target Defense (Cmu-Isr-14-109), Bradley Schmerl, Javier Camara, Gabriel Moreno, David Garlan, Andrew O. Mellinger Sep 2017

Architecture-Based Self-Adaptation For Moving Target Defense (Cmu-Isr-14-109), Bradley Schmerl, Javier Camara, Gabriel Moreno, David Garlan, Andrew O. Mellinger

Gabriel A. Moreno

The fundamental premise behind Moving Target Defense (MTD) is to create a dynamic and shifting system that is more difficult to attack than a static system because a constantly changing attack surface at least reduces the chance of an attacker finding and exploiting the weakness. However, MTD approaches are typically chosen without regard to other qualities of the system, such as performance or cost. This report explores the use of self-adaptive systems, in particular those based on the architecture of the running system. A systems software architecture can be used to trade off different quality dimensions of the system. In …

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Comparing Model-Based Predictive Approaches To Self-Adaptation: Cobra And Pla, Gabriel A. Moreno, Alessandro V. Papadopoulos, Konstantinos Angelopoulos, Javier Camara, Bradley Schmerl Apr 2017

Comparing Model-Based Predictive Approaches To Self-Adaptation: Cobra And Pla, Gabriel A. Moreno, Alessandro V. Papadopoulos, Konstantinos Angelopoulos, Javier Camara, Bradley Schmerl

Gabriel A. Moreno

Modern software-intensive systems must often guarantee certain quality requirements under changing run-time conditions and high levels of uncertainty. Self-adaptation has proven to be an effective way to engineer systems that can address such challenges, but many of these approaches are purely reactive and adapt only after a failure has taken place. To overcome some of the limitations of reactive approaches (e.g., lagging behind environment changes and favoring short-term improvements), recent proactive self-adaptation mechanisms apply ideas from control theory, such as model predictive control (MPC), to improve adaptation. When selecting which MPC approach to apply, the improvement that can be obtained …

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Hybrid Planning For Decision Making In Self-Adaptive Systems, Ashutosh Pandey, Gabriel A. Moreno, Javier Camara, David Garlan Aug 2016

Hybrid Planning For Decision Making In Self-Adaptive Systems, Ashutosh Pandey, Gabriel A. Moreno, Javier Camara, David Garlan

Gabriel A. Moreno

Run-time generation of adaptation plans is a powerful mechanism that helps a self-adaptive system to meet its goals in a dynamically changing environment. In the past, researchers have demonstrated successful use of various automated planning techniques to generate adaptation plans at run time. However, for a planning technique, there is often a trade-off between timeliness and optimality of the solution. For some self-adaptive systems, ideally, one would like to have a planning approach that is both quick and finds an optimal adaptation plan. To find the right balance between these conflicting requirements, this paper introduces a hybrid planning approach that …

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Efficient Decision-Making Under Uncertainty For Proactive Self-Adaptation, Gabriel A. Moreno, Javier Camara, David Garlan, Bradley Schmerl Jul 2016

Efficient Decision-Making Under Uncertainty For Proactive Self-Adaptation, Gabriel A. Moreno, Javier Camara, David Garlan, Bradley Schmerl

Gabriel A. Moreno

Proactive latency-aware adaptation is an approach for self-adaptive systems that improves over reactive adaptation by considering both the current and anticipated adaptation needs of the system, and taking into account the latency of adaptation tactics so that they can be started with the necessary lead time. Making an adaptation decision with these characteristics requires solving an optimization problem to select the adaptation path that maximizes an objective function over a finite look-ahead horizon. Since this is a problem of selecting adaptation actions in the context of the probabilistic behavior of the environment, Markov decision processes (MDP) are a suitable approach. …

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Analyzing Latency-Aware Self-Adaptation Using Stochastic Games And Simulations, Javier Camara, Gabriel A. Moreno, David Garlan, Bradley Schmerl Dec 2014

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 …

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Proactive Self-Adaptation Under Uncertainty: A Probabilistic Model Checking Approach, Gabriel A. Moreno, Javier Camara, David Garlan, Bradley Schmerl Dec 2014

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 …

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Reasoning About Human Participation In Self-Adaptive Systems, Javier Camara, Gabriel A. Moreno, David Garlan Dec 2014

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 …

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