11 research outputs found

    Using Semantic Web Services for AI-Based Research in Industry 4.0

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    The transition to Industry 4.0 requires smart manufacturing systems that are easily configurable and provide a high level of flexibility during manufacturing in order to achieve mass customization or to support cloud manufacturing. To realize this, Cyber-Physical Systems (CPSs) combined with Artificial Intelligence (AI) methods find their way into manufacturing shop floors. For using AI methods in the context of Industry 4.0, semantic web services are indispensable to provide a reasonable abstraction of the underlying manufacturing capabilities. In this paper, we present semantic web services for AI-based research in Industry 4.0. Therefore, we developed more than 300 semantic web services for a physical simulation factory based on Web Ontology Language for Web Services (OWL-S) and Web Service Modeling Ontology (WSMO) and linked them to an already existing domain ontology for intelligent manufacturing control. Suitable for the requirements of CPS environments, our pre- and postconditions are verified in near real-time by invoking other semantic web services in contrast to complex reasoning within the knowledge base. Finally, we evaluate our implementation by executing a cyber-physical workflow composed of semantic web services using a workflow management system.Comment: Submitted to ISWC 202

    Toward an Adaptive Enterprise Modelling Platform

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    For the past three decades, enterprise modelling (EM) has been emerging as a significant yet complex paradigm to tackle holistic systematic enterprise analysis and design. With a high fluctuation in the global economy, industrial stability and technology shift, the necessity of such paradigms becomes crucial in determining the decisions that an enterprise can make for surviving in such a highly dynamic business ecosystem. EM practices have focused for a long time, on the design-time of enterprise systems. Recently, there has been a rapid development in data analytics, machine learning and intelligent systems from which an EM platform can benefit. EM needs to cope with the new changes in both business and technology; it should also help architects to determine optimum decisions and reduce complexity in technical infrastructure. In this paper, the author discusses several challenges facing enterprise modelling practices and offers an architectural notion for future development focusing on the requirements of a platform that can be called intelligent and adaptive

    A Response-aware Traffic Offloading Scheme using Regression Machine Learning for User-Centric Large-Scale Internet of Things

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    Resource allocation and management in an Internet of Things (IoT) paradigm requires precise request and response processing irrespective of its scalability support. Unpredictable traffic patterns and user density demands reliable offloading for handling user request traffic and service response. Considering the need for large-scale IoT in an account of its interoperability and heterogeneous support, this manuscript introduces a response-aware traffic offloading scheme (RTOS) for delay-sensitive user requests. This offloading scheme is supported by a multivariate spline regression machine learning model for classifying traffic for reducing the failure rate. The splines are adaptive based on the classified traffic for performing independent and shared offloading. The computation process for determining the offloading model is inherited from the cyber-physical system (CPS) coupled with the IoT-Cloud architecture. The information from the knowledge base and event logs are exploited for decision-making in employing the offloading method for the classified traffic. The simulation analysis of this scheme shows that it is effective in improving the request processing ratio and reducing processing, response time, and delay. The simulation is performed for the varying user density and traffic flows

    Protocol for a Systematic Literature Review on Adaptative Middleware Support for IoT and CPS

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    This protocol defines the procedure to conduct a systematic literature review on adaptive middleware support for the Internet of Things (IoT) and Cyber-physical Systems (CPS). The mentioned concepts deal with smart interactive objects which provide a set of services, but they look into the problem from various perspectives. We especially look into middleware design decisions for reactive/proactive adaptations. Following a systematic literature review (SLR) in the selection procedure, we selected 62 papers among 4,274 candidate studies. To this end, we applied the classification and extraction framework to select and analyze the most influential domain-related information. In addition to the academic database, we took advantage of the use-cases provided by our industrial partners within the CPS4EU 2 project. This document clarifies the primary studies' selection process. The analysis of the studies, discussion, and solution proposals will be presented separately in a journal article

    Cyber-Physical Systems and Smart Cities in India: Opportunities, Issues, and Challenges

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    A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used in almost every system component within a smart city ecosystem. This paper attempts to discuss the key components and issues involved in transforming conventional cities into smart cities with a special focus on cyber-physical systems in the Indian context. The paper primarily focuses on the infrastructural facilities and technical knowhow to smartly convert classical cities that were built haphazardly due to overpopulation and ill planning into smart cities. It further discusses cyber-physical systems as a core component of smart city setups, highlighting the related security issues. The opportunities for businesses, governments, inhabitants, and other stakeholders in a smart city ecosystem in the Indian context are also discussed. Finally, it highlights the issues and challenges concerning technical, financial, and other social and infrastructural bottlenecks in the way of realizing smart city concepts along with future research directions

    A survey of secure middleware for the Internet of Things

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    The rapid growth of small Internet connected devices, known as the Internet of Things (IoT), is creating a new set of challenges to create secure, private infrastructures. This paper reviews the current literature on the challenges and approaches to security and privacy in the Internet of Things, with a strong focus on how these aspects are handled in IoT middleware. We focus on IoT middleware because many systems are built from existing middleware and these inherit the underlying security properties of the middleware framework. The paper is composed of three main sections. Firstly, we propose a matrix of security and privacy threats for IoT. This matrix is used as the basis of a widespread literature review aimed at identifying requirements on IoT platforms and middleware. Secondly, we present a structured literature review of the available middleware and how security is handled in these middleware approaches. We utilise the requirements from the first phase to evaluate. Finally, we draw a set of conclusions and identify further work in this area

    A survey of secure middleware for the Internet of Things

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