The Experts below are selected from a list of 34569 Experts worldwide ranked by ideXlab platform
Wijnand Derks - One of the best experts on this subject based on the ideXlab platform.
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requirements engineering for e government services a citizen Centric Approach and case study
Government Information Quarterly, 2009Co-Authors: Lex Van Velsen, Thea Van Der Geest, Marc J Ter Hedde, Wijnand DerksAbstract:Throughout the last decade, user involvement in e-Government service design has been virtually non-existent. Over time, e-Government experts began to realize that these services would benefit from a citizen-Centric requirements engineering Approach which has led to a demand for such an Approach for this particular field. This article presents a citizen-Centric Approach towards user requirements engineering for e-Government services. It utilizes interviews and citizen walkthroughs of low-fidelity prototypes. A case study of a social support portal illustrates the Approach and shows the need for repeated citizen inquiry, as the implementation of user requirements in low-fidelity prototype design is not always accepted by prospective end-users.
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Requirements engineering for e-Government services: A citizen-Centric Approach and case study
Government Information Quarterly, 2009Co-Authors: Lex Van Velsen, Marc Ter Hedde, Thea Van Der Geest, Wijnand DerksAbstract:Throughout the last decade, user involvement in e-Government service design has been virtually non-existent. Over time, e-Government experts began to realize that these services would benefit from a citizen-Centric requirements engineering Approach which has led to a demand for such an Approach for this particular field. This article presents a citizen-Centric Approach towards user requirements engineering for e-Government services. It utilizes interviews and citizen walkthroughs of low-fidelity prototypes. A case study of a social support portal illustrates the Approach and shows the need for repeated citizen inquiry, as the implementation of user requirements in low-fidelity prototype design is not always accepted by prospective end-users. © 2009 Elsevier Inc. All rights reserved.
Serge Haziyev - One of the best experts on this subject based on the ideXlab platform.
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Agile big data analytics development: An architecture-Centric Approach
Proceedings of the Annual Hawaii International Conference on System Sciences, 2016Co-Authors: Hong Mei Chen, Rick Kazman, Serge HaziyevAbstract:Agile development for big data analytics has become the new normal. However, research questions remain: 1) how should a big data system be designed and developed to effectively support advanced analytics? and 2) how should the agile process be adapted for big data analytics development? This article contributes an Architecture-Centric Agile Big data Analytics (AABA) development methodology evolved and validated in 10 case studies through Collaborative Practice Research. Our studies showed that architecture agility is the key for successful agile big data analytics development. Employing an architecture-Centric Approach, the AABA methodology integrates the Big Data system Design (BDD) method and Architecture-Centric Agile Analytics with architecture-supported DevOps (AAA) model for effective value discovery and rapid continuous delivery of value. The uses of a design concepts catalog and architectural spikes are advancements to architecture design methods that have proven to be critical to agile big data analytics development.
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Agile Big Data Analytics for Web-Based Systems: An Architecture-Centric Approach
IEEE Transactions on Big Data, 2016Co-Authors: Hong Mei Chen, Rick Kazman, Serge HaziyevAbstract:This article contributes an architecture-Centric methodology, called AABA (Architecture-Centric Agile Big data Analytics), to address the technical, organizational, and rapid technology change challenges of both big data system development and agile delivery of big data analytics for Web-based Systems (WBS). As the first of its kind, AABA fills a methodological void by adopting an architecture-Centric Approach, advancing and integrating software architecture analysis and design, big data modeling and agile practices. This article describes how AABA was developed, evolved and validated simultaneously in 10 empirical WBS case studies through 3 CPR (Collaborative Practice Research) cycles. In addition, this article presents an 11th case study illustrating the processes, methods and techniques/tools in AABA for cost-effectively achieving business goals and architecture agility in a large scale WBS. All 11 case studies showed that architecture-Centric design, development, and operation is key to taming technical complexity and achieving agility necessary for successful WBS big data analytics development. Our contribution is novel and important. The use of reference architectures, a design concepts catalog and architectural spikes in AABA are advancements to architecture design methods. In addition, our architecture-Centric Approach to DevOps was critical for achieving strategic control over continuous big data value delivery for WBS.
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Agile Big Data Analytics for Web-Based Systems: An Architecture-Centric Approach
IEEE Transactions on Big Data, 2016Co-Authors: Hong Mei Chen, Rick Kazman, Serge HaziyevAbstract:This article contributes an architecture-Centric methodology, called AABA (Architecture-Centric Agile Big data Analytics), to address the technical, organizational, and rapid technology change challenges of both big data system development and agile delivery of big data analytics for Web-based Systems (WBS). As the first of its kind, AABA fills a methodological void by adopting an architecture-Centric Approach, advancing and integrating software architecture analysis and design, big data modeling and agile practices. This article describes how AABA was developed, evolved and validated simultaneously in 10 empirical WBS case studies through three CPR (Collaborative Practice Research) cycles. In addition, this article presents an 11th case study illustrating the processes, methods and techniques/tools in AABA for cost-effectively achieving business goals and architecture agility in a large scale WBS. All 11 case studies showed that architecture-Centric design, development, and operation is key to taming technical complexity and achieving agility necessary for successful WBS big data analytics development. Our contribution is novel and important. The use of reference architectures, a design concepts catalog and architectural spikes in AABA are advancements to architecture design methods. In addition, our architecture-Centric Approach to DevOps was critical for achieving strategic control over continuous big data value delivery for WBS.
Michael Oboyle - One of the best experts on this subject based on the ideXlab platform.
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microarchitectural design space exploration using an architecture Centric Approach
International Symposium on Microarchitecture, 2007Co-Authors: Christophe Dubach, Timothy M Jones, Michael OboyleAbstract:The microarchitectural design space of a new processor is too large for an architect to evaluate in its entirety. Even with the use of statistical simulation, evaluation of a single configuration can take excessive time due to the need to run a set of benchmarks with realistic workloads. This paper proposes a novel machine learning model that can quickly and accurately predict the performance and energy consumption of any set of programs on any microarchitectural configuration. This architecture-Centric Approach uses prior knowledge from off-line training and applies it across benchmarks. This allows our model to pre- dict the performance of any new program across the entire microarchitecture configuration space with just 32 further simulations. We compare our Approach to a state-of-the-art program- specific predictor and show that we significantly reduce pre- diction error. We reduce the average error when predicting performance from 24% to just 7% and increase the cor- relation coefficient from 0.55 to 0.95. We then show that this predictor can be used to guide the search of the design space, selecting the best configuration for energy-delay in just 3 further simulations, reducing it to 0.85. We also eval- uate the cost of off-line learning and show that we can still achieve a high level of accuracy when using just 5 bench- marks to train. Finally, we analyse our design space and show how different microarchitectural parameters can af- fect the cycles, energy and energy-delay of the architectural configurations.
R.j. Adensamer - One of the best experts on this subject based on the ideXlab platform.
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A process-Centric Approach to enterprise transformation
Proceedings of NOMS '96 - IEEE Network Operations and Management Symposium, 1996Co-Authors: R.j. AdensamerAbstract:Telecommunications service providers are faced with a rapidly changing business environment. They are being pushed to deal with global competition, reducing the cost of doing business, and rapidly developing new products and services. To meet these challenges, they must constantly modify their enterprise to optimize the way in which they do business. Business process re-engineering and continuous improvement methods target both the radical and continuous improvement of enterprise effectiveness. Because of the scope of change, the term "enterprise transformation" is often used to describe the scope of change required to organizations and systems. The paper presents a process-Centric Approach to addressing enterprise transformation. A process-Centric Approach is favoured because it is evolvable, scaleable, interoperable, modular and reconfigurable. The proposed solution, which encompasses the principles of a process-Centric Approach, has two levels of processes; local and global (enterprise). Local processes manage the presentation aspects in the user context. Enterprise level processes manage the overall information integration aspects. The paper describes a process-Centric support system architecture that facilitates enterprise transformation. To maximize flexibility, processes are architecturally separated from the data required to support the execution of the process. This Approach provides an architectural framework to flexibly support enterprise transformation.
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NOMS - A process-Centric Approach to enterprise transformation
Proceedings of NOMS '96 - IEEE Network Operations and Management Symposium, 1996Co-Authors: R.j. AdensamerAbstract:Telecommunications service providers are faced with a rapidly changing business environment. They are being pushed to deal with global competition, reducing the cost of doing business, and rapidly developing new products and services. To meet these challenges, they must constantly modify their enterprise to optimize the way in which they do business. Business process re-engineering and continuous improvement methods target both the radical and continuous improvement of enterprise effectiveness. Because of the scope of change, the term "enterprise transformation" is often used to describe the scope of change required to organizations and systems. The paper presents a process-Centric Approach to addressing enterprise transformation. A process-Centric Approach is favoured because it is evolvable, scaleable, interoperable, modular and reconfigurable. The proposed solution, which encompasses the principles of a process-Centric Approach, has two levels of processes; local and global (enterprise). Local processes manage the presentation aspects in the user context. Enterprise level processes manage the overall information integration aspects. The paper describes a process-Centric support system architecture that facilitates enterprise transformation. To maximize flexibility, processes are architecturally separated from the data required to support the execution of the process. This Approach provides an architectural framework to flexibly support enterprise transformation.
Christophe Dubach - One of the best experts on this subject based on the ideXlab platform.
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An Empirical Architecture-Centric Approach to Microarchitectural Design Space Exploration
IEEE Transactions on Computers, 2011Co-Authors: Christophe Dubach, Timothy M Jones, Michael F.p. O'boyleAbstract:The microarchitectural design space of a new processor is too large for an architect to evaluate in its entirety. Even with the use of statistical simulation, evaluation of a single configuration can take an excessive amount of time due to the need to run a set of benchmarks with realistic workloads. This paper proposes a novel machine-learning model that can quickly and accurately predict the performance and energy consumption of any new program on any microarchitectural configuration. This architecture-Centric Approach uses prior knowledge from offline training and applies it across benchmarks. This allows our model to predict the performance of any new program across the entire microarchitecture configuration space with just 32 further simulations. First, we analyze our design space and show how different microarchitectural parameters can affect the cycles, energy, energy-delay (ED), and energy-delay-squared (EDD) of the architectural configurations. We show the accuracy of our predictor on SPEC CPU 2000 and how it can be used to predict programs from a different benchmark suite. We then compare our Approach to a state-of-the-art program-specific predictor and show that we significantly reduce prediction error. We reduce the average error when predicting performance from 24 percent to just seven percent and increase the correlation coefficient from 0.55 to 0.95. Finally, we evaluate the cost of offline learning and show that we can still achieve a high coefficient of correlation when using just five benchmarks to train.
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microarchitectural design space exploration using an architecture Centric Approach
International Symposium on Microarchitecture, 2007Co-Authors: Christophe Dubach, Timothy M Jones, Michael OboyleAbstract:The microarchitectural design space of a new processor is too large for an architect to evaluate in its entirety. Even with the use of statistical simulation, evaluation of a single configuration can take excessive time due to the need to run a set of benchmarks with realistic workloads. This paper proposes a novel machine learning model that can quickly and accurately predict the performance and energy consumption of any set of programs on any microarchitectural configuration. This architecture-Centric Approach uses prior knowledge from off-line training and applies it across benchmarks. This allows our model to pre- dict the performance of any new program across the entire microarchitecture configuration space with just 32 further simulations. We compare our Approach to a state-of-the-art program- specific predictor and show that we significantly reduce pre- diction error. We reduce the average error when predicting performance from 24% to just 7% and increase the cor- relation coefficient from 0.55 to 0.95. We then show that this predictor can be used to guide the search of the design space, selecting the best configuration for energy-delay in just 3 further simulations, reducing it to 0.85. We also eval- uate the cost of off-line learning and show that we can still achieve a high level of accuracy when using just 5 bench- marks to train. Finally, we analyse our design space and show how different microarchitectural parameters can af- fect the cycles, energy and energy-delay of the architectural configurations.