Model Driven
52289805
Model Driven Deep Learning for Physical Layer Communications
Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and has demonstrated an impressive performance improvement in recent years. However, most existing works related to DL focus on data driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, model driven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted.
IEEE Wireless Communications
Hengtao He Shi Jin Chao-Kai Wen Feifei Gao Geoffrey Y Li Zongben Xu
52822294
A Model Driven Deep Learning Network for MIMO Detection
In this paper, we propose a model driven deep learning network for multiple input multiple output (MIMO) detection. The structure of the network is specially designed by unfolding the iterative algorithm. Some trainable parameters are optimized through deep learning techniques to improve the detection performance. Since the number of trainable variables of the network is equal to that of the layers, the network can be easily trained within a very short time. Furthermore, the network can handle time varying channel with only a single training. Numerical results show that the proposed approach can improve the performance of the iterative algorithm significantly under Rayleigh and correlated MIMO channels.
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
Hengtao He Chao-Kai Wen Shi Jin Geoffrey Y Li
19145695
Challenges of Domain Driven Microservice Design: A Model Driven Perspective
Domain driven design (DDD) is a model driven methodology to capture relevant domain knowledge for software design. It provides the means to isolate domain concepts and identify concept relationships. This makes DDD particularly appropriate for designing microservice architectures, because functional microservices focus on realizing distinct business capabilities. This article explores the challenges of domain driven microservice design and presents ways to cope with them based on model driven development.
IEEE Software
Florian Rademacher Jonas Sorgalla Sabine Sachweh
2267357
Model Driven Engineering
Encyclopedia of GIS
Jean-Marc Jezequel
13850384
A social force evacuation model driven by video data
Abstract This paper proposes a video data driven social force model for simulating crowd evacuation. The initialization of pedestrian position, path navigation, and goal selection in the improved social force model was guided by real video data. To initialize pedestrian position and determine path navigation, the distribution of the pedestrians is set according to the real video. We also extracted the trajectories of pedestrian movement from the videos, and these trajectories were stored into a path set to guide the evacuation of pedestrians. Moreover, a fitness function was defined to model the behavior of a pedestrian goal selection. The fitness function could process the evacuation parameters, which were extracted from the video, and consider the degree and distance of exit congestion. Furthermore, we quantified the relationship values among pedestrians, and a new force called "group force" was added to the primary social force model. Pedestrians with close relationship gathered into one group and walked together. To validate the effectiveness of the proposed method, the video data driven model was applied to simulate campus halls and roads. Simulation results show that the proposed approach is consistent with real world situations and can assist in analyzing emergency evacuation scenarios.
Simul. Model. Pract. Theory
Baoxi Liu Hong Liu H Zhang Xin Qin
6816482
OpenDaylight: Towards a Model Driven SDN Controller architecture
This paper describes a novel Software Defined Networking (SDN) Controller architecture that is built on Model Driven Software Engineering (MDSE) principles. It supports both the "classic" OpenFlow based approach to SDN and emerging model driven network management/programmability technologies, such as NETCONF/YANG. The architecture was first implemented in the OpenDaylight Project Hydrogen release, and it is being further evolved in subsequent OpenDaylight releases.
Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014
Jan Medved Robert Varga Anton Tkacik Ken Gray
3404182
User Experience for Model Driven Engineering: Challenges and Future Directions
Since its infancy, Model Driven Engineering (MDE) research has primarily focused on technical issues. Although it is becoming increasingly common for MDE research papers to evaluate their theoretical and practical solutions, extensive usability studies are still uncommon. We observe a scarcity of User eXperience (UX) related research in the MDE community, and posit that many existing tools and languages have room for improvement with respect to UX [26] [44] [37] where UX is a key focus area in the software development industry. We consider this gap a fundamental problem that needs to be addressed by the community if MDE is to gain widespread use. In this vision paper, we explore how and where UX fits into MDE by considering motivating use cases that revolve around different dimensions of integration: model integration, tool integration, and integration between process and tool support. Based on the literature and our collective experience in research and industrial collaborations, we propose future directions for addressing these challenges.
2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS)
Silvia Mara Abrahao Francis Bourdeleau Betty H C Cheng Sahar Kokaly Richard F Paige Harald Storrle Jon Whittle
21632806
Model driven engineering: A survey supported by the unified conceptual model
During the last decade a new trend of approaches has emerged, which considers models not just documentation artefacts, but also central artefacts in the software engineering field, allowing the creation or automatic execution of software systems starting from those models. These proposals have been classified generically as Model Driven Engineering (MDE) and share common concepts and terms that need to be abstracted, discussed and understood. This paper presents a survey on MDE based on a unified conceptual model that clearly identifies and relates these essential concepts, namely the concepts of system, model, metamodel, modeling language, transformations, software platform, and software product. In addition, this paper discusses the terminologies relating MDE, MDD, MDA and others. This survey is based on earlier work, however, contrary to those, it intends to give a simple, broader and integrated view of the essential concepts and respective terminology commonly involved in the MDE, answering to key questions such as: What is a model? What is the relation between a model and a metamodel? What are the key facets of a modeling language? How can I use models in the context of a software development process? What are the relations between models and source code artefacts and software platforms? and What are the relations between MDE, MDD, MDA and other MD approaches?
Comput. Lang. Syst. Struct.
Alberto Rodrigues da Silva
7612918
Model Driven Reverse Engineering Approaches: A Systematic Literature Review
This paper explores and describes the state of the art for what concerns the model driven approaches proposed in the literature to support reverse engineering. We conducted a systematic literature review on this topic with the aim to answer three research questions. We focus on various solutions developed for model driven reverse engineering, outlining in particular the models they use and the transformations applied to the models. We also consider the tools used for model definition, extraction, and transformation and the level of automation reached by the available tools. The model driven reverse engineering approaches are also analyzed based on various features such as genericity, extensibility, automation of the reverse engineering process, and coverage of the full or partial source artifacts. We describe in detail and compare fifteen approaches applying model driven reverse engineering. Based on this analysis, we identify and indicate some hints on choosing a model driven reverse engineering approach from the available ones, and we outline open issues concerning the model driven reverse engineering approaches.
IEEE Access
Claudia Raibulet Francesca Arcelli Fontana Marco Zanoni
36176571
Model Driven Software Engineering in Practice
This book discusses how model based approaches can improve the daily practice of software professionals. This is known as Model Driven Software Engineering (MDSE) or, simply, Model Driven Engineering (MDE) MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g. due to the convergence of software development and business analysis. The aim of this book is to provide you with an agile and flexible tool to introduce you to the MDSE world, thus allowing you to quickly understand its basic principles and techniques and to choose the right set of MDSE instruments for your needs so that you can start to benefit from MDSE right away. The book is organized into two main parts. The first part discusses the foundations of MDSE in terms of basic concepts (i.e. models and transformations) driving principles, application scenarios and current standards, like the well known MDA initiative proposed by OMG (Object Management Group) as well as the practices on how to integrate MDSE in existing development processes. The second part deals with the technical aspects of MDSE, spanning from the basics on when and how to build a domain specific modeling language, to the description of Model to Text and Model to Model transformations, and the tools that support the management of MDSE projects. The book is targeted to a diverse set of readers, spanning: professionals, CTOs, CIOs, and team managers that need to have a bird's eye vision on the matter, so as to take the appropriate decisions when it comes to choosing the best development techniques for their company or team; software analysts, developers, or designers that expect to use MDSE for improving everyday work productivity, either by applying the basic modeling techniques and notations or by defining new domain specific modeling languages and applying end to end MDSE practices in the software factory; and academic teachers and students to address undergrad and postgrad courses on MDSE. In addition to the contents of the book, more resources are provided on the book's website http:/www.mdse book.com/ including the examples presented in the book. Table of Contents: Introduction MDSE Principles MDSE Use Cases Model Driven Architecture (MDA) Integration of MDSE in your Development Process Modeling Languages at a Glance Developing your Own Modeling Language Model to Model Transformations Model to Text Transformations Managing Models Summary
Synthesis Lectures on Software Engineering
Marco Brambilla Jordi Cabot Manuel Wimmer