The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Nelly Bencomo - One of the best experts on this subject based on the ideXlab platform.
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Towards History-Aware Self-Adaptation with Explanation Capabilities
2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2019Co-Authors: Antonio Garcia Dominguez, Nelly Bencomo, Juan Marcelo Parra Ullauri, Luis Hernan Garcia PaucarAbstract:Self-Adaptive Systems (SAS) increasingly use techniques such as AI-based learning and evolutionary programming. In this paper, we argue that a SAS needs an infrastructure and capabilities to look at its own history to explain and reason why the System has reached its current state and exhibits its current behaviour. Achieving this is no simple feat: there are different challenges with respect to the feasibility of storing past System history, querying it and applying the information in the context of a given decision-making algorithm. We introduce 4 levels of capabilities that should be exposed by reflective, self aware and Self-Adaptive Systems, and which will guide our future research on the topic in the longer term. We demonstrate our results for the first two levels using temporal graph-based models. Specifically, we explain how the first level covers forensic analysis of the execution results. This is followed by the description of our results in enabling historical analyses while the Self-Adaptive System is running, based on the capabilities provided by the second level. Required System architectures are also proposed, as well as the overheads that would be imposed by live analysis. Research opportunities provided by the set of levels are also discussed.
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Knowledge Base K Models to Support Trade-Offs for Self-Adaptation using Markov Processes
2019 IEEE 13th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2019Co-Authors: Luis Hernan Garcia Paucar, Nelly BencomoAbstract:Runtime models support decision-making and reasoning for self-adaptation based on both design-time knowledge and information that may emerge at runtime. In this paper, we demonstrate a novel use of Partially Observable Markov Decision Processes (POMDPs) as runtime models to support the decision-making of a Self Adaptive System (SAS) in the context of the MAPE-K loop. The trade-off between the non-functional requirements (NFRs) has been embodied as a POMDP in the context of the MAPE-K loop. Using Bayesian learning, the levels of satisficement of the NFRs are inferred and updated during execution in the form of runtime models in the Knowledge Base. We evaluate our work with a case study of the networking application domain.
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Perpetual Assurances for Self-Adaptive Systems
arXiv: Software Engineering, 2019Co-Authors: Danny Weyns, Nelly Bencomo, Javier Cámara, Carlo Ghezzi, Paola Inverardi, Radu Calinescu, Vincenzo Grassi, Lars Grunske, Jean-marc Jézéquel, Sam MalekAbstract:Providing assurances for Self-Adaptive Systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the Self-Adaptive System complies with its requirements calls for an enduring process spanning the whole lifetime of the System. In this process, humans and the System jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for Self-Adaptive Systems. In this paper, we provide a background framework and the foundation for perpetual assurances for Self-Adaptive Systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation.
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Software Engineering for Self-Adaptive Systems - Perpetual Assurances for Self-Adaptive Systems
Lecture Notes in Computer Science, 2017Co-Authors: Danny Weyns, Nelly Bencomo, Javier Cámara, Carlo Ghezzi, Paola Inverardi, Radu Calinescu, Vincenzo Grassi, Lars Grunske, Jean-marc Jézéquel, Sam MalekAbstract:Providing assurances for Self-Adaptive Systems is challenging. A primary underlying problem is uncertainty that may stem from a variety of different sources, ranging from incomplete knowledge to sensor noise and uncertain behavior of humans in the loop. Providing assurances that the Self-Adaptive System complies with its requirements calls for an enduring process spanning the whole lifetime of the System. In this process, humans and the System jointly derive and integrate new evidence and arguments, which we coined perpetual assurances for Self-Adaptive Systems. In this paper, we provide a background framework and the foundation for perpetual assurances for Self-Adaptive Systems. We elaborate on the concrete challenges of offering perpetual assurances, requirements for solutions, realization techniques and mechanisms to make solutions suitable. We also present benchmark criteria to compare solutions. We then present a concrete exemplar that researchers can use to assess and compare approaches for perpetual assurances for self-adaptation.
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Self-Explanation in Adaptive Systems
2012 IEEE 17th International Conference on Engineering of Complex Computer Systems, 2012Co-Authors: Nelly Bencomo, Pete Sawyer, Kris Welsh, Jon WhittleAbstract:The behaviour of self adaptive Systems can be emergent. The difficulty in predicting the System's behaviour means that there is scope for the System to surprise its customers and its developers. Because its behaviour is emergent, a Self-Adaptive System needs to garner confidence in its customers and it needs to resolve any surprise on the part of the developer during testing and mainteinance. We believe that these two functions can only be achieved if a Self-Adaptive System is also capable of self-explanation. We argue a Self-Adaptive System's behaviour needs to be explained in terms of satisfaction of its requirements. Since Self-Adaptive System requirements may themselves be emergent, a means needs to be found to explain the current behaviour of the System and the reasons that brought that behaviour about. We propose the use of goal-based models during runtime to offer self-explanation of how a System is meeting its requirements, and why the means of meeting these were chosen. We discuss the results of early experiments in self-explanation, and set out future work.
Bradley Schmerl - One of the best experts on this subject based on the ideXlab platform.
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RADIANCE 2015 Keynote: Challenges in Engineering Dependable Self-Adaptive System
2015 IEEE International Conference on Dependable Systems and Networks Workshops, 2015Co-Authors: Bradley SchmerlAbstract:To provide some levels of dependency in software Systems, Self-Adaptive Systems have been proposed as a principled approach to engineering software Systems to adapt Systems to meet requirements even in the face of changes and uncertainty in the environment. But how can we show that changing a System at run time will make Systems more dependable? In this keynote, I will outline a set of challenges for providing assurances for Self-Adaptive Systems, and describe work that our group has been doing that can provide evidence for assurances in a number of contexts, including collaborative self-adaptation with humans-in-the-loop. I will discuss how probabilistic model checking can be used to explore the state space of Self-Adaptive Systems, and how they can provide more realistic models of the impacts that adapting a System may have on the System.
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DSN Workshops - RADIANCE 2015 Keynote: Challenges in Engineering Dependable Self-Adaptive System
2015 IEEE International Conference on Dependable Systems and Networks Workshops, 2015Co-Authors: Bradley SchmerlAbstract:To provide some levels of dependency in software Systems, Self-Adaptive Systems have been proposed as a principled approach to engineering software Systems to adapt Systems to meet requirements even in the face of changes and uncertainty in the environment. But how can we show that changing a System at run time will make Systems more dependable? In this keynote, I will outline a set of challenges for providing assurances for Self-Adaptive Systems, and describe work that our group has been doing that can provide evidence for assurances in a number of contexts, including collaborative self-adaptation with humans-in-the-loop. I will discuss how probabilistic model checking can be used to explore the state space of Self-Adaptive Systems, and how they can provide more realistic models of the impacts that adapting a System may have on the System.
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Evaluating the effectiveness of the Rainbow Self-Adaptive System
2009 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, 2009Co-Authors: Shang-wen Cheng, David Garlan, Bradley SchmerlAbstract:Rainbow is a framework for engineering a System with run-time, Self-Adaptive capabilities to monitor, detect, decide, and act on opportunities for System improvement. We applied Rainbow to a System, Znn.com, and evaluated its effectiveness to self-adapt on three levels: its effectiveness to maintain quality attribute in the face of changing conditions, run-time overheads of adaptation, and the engineering effort to use it to add Self-Adaptive capabilities to Znn.com. We make Znn.com and the associated evaluation tools available to the community so that other researchers can use it to evaluate their own Systems and the community can compare different Systems. In this paper, we report on our evaluation experience, reflect on some principles for benchmarking Self-Adaptive Systems, and discuss the suitability of our evaluation tools for this purpose.
Christian Becker - One of the best experts on this subject based on the ideXlab platform.
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Runtime Evolution of the Adaptation Logic in Self-Adaptive Systems
2015 IEEE International Conference on Autonomic Computing, 2015Co-Authors: Felix Maximilian Roth, Christian Krupitzer, Christian BeckerAbstract:Self-Adaptive Systems, which are highly related to Autonomic Computing, are a response to the increasing complexity and size of information Systems. They are able to adapt their behavior to changes in the environment or System resources. A Self-Adaptive System consists of managed resources that realize functionality and an adaptation logic that controls the adaptations. So far, many research has been performed on adapting the managed resources. However, only few works cover adapting the adaptation logic, which might be necessary in several cases, e.g., When the architecture of the managed resources changes. This work adresses why adaptation of the adaptation logic might be beneficial, how it can be achieved, and what challenges arise.
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ICAC - Runtime Evolution of the Adaptation Logic in Self-Adaptive Systems
2015 IEEE International Conference on Autonomic Computing, 2015Co-Authors: Felix Maximilian Roth, Christian Krupitzer, Christian BeckerAbstract:Self-Adaptive Systems, which are highly related to Autonomic Computing, are a response to the increasing complexity and size of information Systems. They are able to adapt their behavior to changes in the environment or System resources. A Self-Adaptive System consists of managed resources that realize functionality and an adaptation logic that controls the adaptations. So far, many research has been performed on adapting the managed resources. However, only few works cover adapting the adaptation logic, which might be necessary in several cases, e.g., When the architecture of the managed resources changes. This work adresses why adaptation of the adaptation logic might be beneficial, how it can be achieved, and what challenges arise.
C. Antill - One of the best experts on this subject based on the ideXlab platform.
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Extreme Temperature Electronics based on Self-Adaptive System using Field Programmable Gate Array
2007 IEEE Aerospace Conference, 2007Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on Commercial-Off-The-Shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) show the change over temperature of the response of the RAA for all possible bias voltage and demonstrate the feasibility of this approach.
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Self-Adaptive System Based on Field Programmable Gate Array for Extreme Temperature Electronics
First NASA ESA Conference on Adaptive Hardware and Systems (AHS'06), 2006Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120 degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on commercial-off-the-shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) demonstrate the feasibility of this approach
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AHS - Self-Adaptive System Based on Field Programmable Gate Array for Extreme Temperature Electronics
First NASA ESA Conference on Adaptive Hardware and Systems (AHS'06), 2006Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120 degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on commercial-off-the-shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) demonstrate the feasibility of this approach
D. Keymeulen - One of the best experts on this subject based on the ideXlab platform.
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Self-repairing and tuning reconfigurable electronics for space
13th IEEE Symposium on Design and Diagnostics of Electronic Circuits and Systems, 2010Co-Authors: D. KeymeulenAbstract:Space missions often require technologies not yet available for earth applications. This talk will present the development of self-reconfigurable electronics for two real-world problems met by NASA: extreme environment electronics and navigation grade miniaturized inertial measurement sensor. Radiation and extreme-temperature hardened electronics is needed to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. This presentation will demonstrate the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters which can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). The second application is related to the development of inexpensive, navigation grade, miniaturized inertial measurement unit (IMU), which surpasses the current state-of-the art in performance, compactness (both size and mass) and power efficiency used by all NASA missions. The talk will explain a self-tuning method for reconfigurable Micro-Electro-Mechanical Systems (MEMS) gyroscopes based on evolutionary computation that has the capacity to efficiently increase the sensitivity of MEMS gyroscopes through in-situ tuning.
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Extreme Temperature Electronics based on Self-Adaptive System using Field Programmable Gate Array
2007 IEEE Aerospace Conference, 2007Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on Commercial-Off-The-Shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) show the change over temperature of the response of the RAA for all possible bias voltage and demonstrate the feasibility of this approach.
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Self-Adaptive System Based on Field Programmable Gate Array for Extreme Temperature Electronics
First NASA ESA Conference on Adaptive Hardware and Systems (AHS'06), 2006Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120 degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on commercial-off-the-shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) demonstrate the feasibility of this approach
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AHS - Self-Adaptive System Based on Field Programmable Gate Array for Extreme Temperature Electronics
First NASA ESA Conference on Adaptive Hardware and Systems (AHS'06), 2006Co-Authors: D. Keymeulen, R. Zebulum, R. Rajeshuni, A. Stoica, S. Katkoori, S. Graves, F. Novak, C. AntillAbstract:Space missions often require radiation and extreme-temperature hardened electronics to survive the harsh environments beyond earth's atmosphere. Traditional approaches to preserve electronics incorporate radiation shielding, insulation and redundancy at the expense of power and weight. In this work, we report the implementation of a Self-Adaptive System using a field programmable gate array (FPGA) and data converters. The Self-Adaptive System can autonomously recover the lost functionality of a reconfigurable analog array (RAA) integrated circuit (IC). Both the RAA IC and the Self-Adaptive System are operating in extreme temperatures (from 120 degC down to -180degC). The RAA IC consists of reconfigurable analog blocks interconnected by several switches and programmable by bias voltages. It implements filters/amplifiers with bandwidth up to 20 MHz. The Self-Adaptive System controls the RAA IC and is realized on commercial-off-the-shelf (COTS) parts. It implements a basic compensation algorithm that corrects a RAA IC in less than a few milliseconds. Experimental results for the cold temperature environment (down to -180degC) demonstrate the feasibility of this approach
