738 research outputs found

    Relational subscription middleware for Internet-scale publish-subscribe

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    The nonlinear inverse problem of electromagnetic induction to recover electrical conductivity is examined. As this is an ill-posed problem based on inaccurate data, there is a strong need to find the reliable features of the models of electrical conductivity. By using optimization theory for an all-at-once approach to inverting frequency-domain electromagnetic data, we attempt to make conclusions about Earth structure under assumptions of one-dimensional and two-dimensional structure. The forward modeling equations are constraints in an optimization problem solving for the fields and the conductivity simultaneously. The computational framework easily allows additional inequality constraints to be imposed.Under the one-dimensional assumption, we develop the optimization approach for use on the magnetotelluric inverse problem. After verifying its accuracy, we use our method to obtain bounds on Earth's average conductivity that all conductivity profiles must obey. There is no regularization required to solve the problem. With the emplacement of additional inequality constraints, we further narrow the bounds. We draw conclusions from a global geomagnetic depth sounding data set and compare with laboratory results, inferring temperature and water content through published Boltzmann-Arrhenius conductivity models.We take the lessons from the 1-D inverse problem and apply them to the 2-D inverse problem. The difficulty of the 2-D inverse problem requires that we first examine our ability to solve the forward problem, where the conductivity structure is known and the fields are unknown. Our forward problem is designed such that we are able to directly transfer it into the optimization approach used for the inversion. With the successful 2-D forward problem as the constraints, a one-dimensional 2-D inverse problem is stepped into a fully 2-D inverse problem for testing purposes. The computational machinery is incrementally modified to meet the challenge of the realistic two-dimensional magnetotelluric inverse problem. We then use two shallow-Earth data sets from different conductivity regimes and invert them for bounded and regularized structure

    Context-Aware Publish Subscribe in Mobile ad Hoc Networks

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    The publish-subscribe communication paradigm is enjoying increasing popularity thanks to its ability to simplify the development of complex distributed applications. However, existing solutions in the publish-subscribe domain address only part of the challenges associated with the development of applications in dynamic scenarios such as mobile ad hoc networks. Mobile applications must be able to assist users in a variety of situations, responding not only to their inputs but also to the characteristics of the environment in which they operate. In this paper, we address these challenges by extending the publish-subscribe paradigm with the ability to manage and exploit context information when matching events against subscriptions. We present our extension in terms of a formal model of context-aware publish-subscribe. We propose a solution for its implementation in MANETs; and finally we validate our approach by means of extensive simulations

    The EnerGAware Middleware Platform

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    IECON 2017, 43rd Annual Conference of the IEEE Industrial Electronics Society (IES). Beijing, China.More and more cyber-physical systems and the internet of things push for a multitude of devices and systems, which need to work together to provide the services as required by the users. Nevertheless, the speed of development and the heterogeneity of devices introduces considerable challenges in the development of such systems. This paper describes a solution being implemented in the setting of a serious game scenario, connected to real homes energy consumption. The solution provides a publish-subscribe middleware which is able to seamlessly connect all the components of the system.info:eu-repo/semantics/publishedVersio

    Towards unified and native enrichment in event processing systems

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    Efficient State Update Exchange in a CPS Environment for Linked Data-based Digital Twins

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    International audienceThis paper addresses the problem of reducing the number of messages needed to exchange state updates between the Cyber-Physical System (CPS) components that integrate with the rest of the CPS through Digital Twins in order to maintain uniform communication interface and carry out their tasks correctly and safely. The main contribution is a proposed architecture and the discussion of its suitability to support correct execution of complex tasks across the CPS. A new State Event Filtering component is presented to provide event-based communication among Digital Twins that are based on the Linked Data principles while keeping the fan-out limited to ensure the scalability of the architecture

    Digital cockpits and decision support systems : design of technics and tools to extract and process data from heterogeneous databases

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    Tableau d'honneur de la Faculté des études supérieures et postdoctorales, 2006-200

    THREE TEMPORAL PERSPECTIVES ON DECENTRALIZED LOCATION-AWARE COMPUTING: PAST, PRESENT, FUTURE

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    Durant les quatre derniĂšres dĂ©cennies, la miniaturisation a permis la diffusion Ă  large Ă©chelle des ordinateurs, les rendant omniprĂ©sents. Aujourd’hui, le nombre d’objets connectĂ©s Ă  Internet ne cesse de croitre et cette tendance n’a pas l’air de ralentir. Ces objets, qui peuvent ĂȘtre des tĂ©lĂ©phones mobiles, des vĂ©hicules ou des senseurs, gĂ©nĂšrent de trĂšs grands volumes de donnĂ©es qui sont presque toujours associĂ©s Ă  un contexte spatiotemporel. Le volume de ces donnĂ©es est souvent si grand que leur traitement requiert la crĂ©ation de systĂšme distribuĂ©s qui impliquent la coopĂ©ration de plusieurs ordinateurs. La capacitĂ© de traiter ces donnĂ©es revĂȘt une importance sociĂ©tale. Par exemple: les donnĂ©es collectĂ©es lors de trajets en voiture permettent aujourd’hui d’éviter les em-bouteillages ou de partager son vĂ©hicule. Un autre exemple: dans un avenir proche, les donnĂ©es collectĂ©es Ă  l’aide de gyroscopes capables de dĂ©tecter les trous dans la chaussĂ©e permettront de mieux planifier les interventions de maintenance Ă  effectuer sur le rĂ©seau routier. Les domaines d’applications sont par consĂ©quent nombreux, de mĂȘme que les problĂšmes qui y sont associĂ©s. Les articles qui composent cette thĂšse traitent de systĂšmes qui partagent deux caractĂ©ristiques clĂ©s: un contexte spatiotemporel et une architecture dĂ©centralisĂ©e. De plus, les systĂšmes dĂ©crits dans ces articles s’articulent autours de trois axes temporels: le prĂ©sent, le passĂ©, et le futur. Les systĂšmes axĂ©s sur le prĂ©sent permettent Ă  un trĂšs grand nombre d’objets connectĂ©s de communiquer en fonction d’un contexte spatial avec des temps de rĂ©ponses proche du temps rĂ©el. Nos contributions dans ce domaine permettent Ă  ce type de systĂšme dĂ©centralisĂ© de s’adapter au volume de donnĂ©e Ă  traiter en s’étendant sur du matĂ©riel bon marchĂ©. Les systĂšmes axĂ©s sur le passĂ© ont pour but de faciliter l’accĂšs a de trĂšs grands volumes donnĂ©es spatiotemporelles collectĂ©es par des objets connectĂ©s. En d’autres termes, il s’agit d’indexer des trajectoires et d’exploiter ces indexes. Nos contributions dans ce domaine permettent de traiter des jeux de trajectoires particuliĂšrement denses, ce qui n’avait pas Ă©tĂ© fait auparavant. Enfin, les systĂšmes axĂ©s sur le futur utilisent les trajectoires passĂ©es pour prĂ©dire les trajectoires que des objets connectĂ©s suivront dans l’avenir. Nos contributions permettent de prĂ©dire les trajectoires suivies par des objets connectĂ©s avec une granularitĂ© jusque lĂ  inĂ©galĂ©e. Bien qu’impliquant des domaines diffĂ©rents, ces contributions s’articulent autour de dĂ©nominateurs communs des systĂšmes sous-jacents, ouvrant la possibilitĂ© de pouvoir traiter ces problĂšmes avec plus de gĂ©nĂ©ricitĂ© dans un avenir proche. -- During the past four decades, due to miniaturization computing devices have become ubiquitous and pervasive. Today, the number of objects connected to the Internet is in- creasing at a rapid pace and this trend does not seem to be slowing down. These objects, which can be smartphones, vehicles, or any kind of sensors, generate large amounts of data that are almost always associated with a spatio-temporal context. The amount of this data is often so large that their processing requires the creation of a distributed system, which involves the cooperation of several computers. The ability to process these data is important for society. For example: the data collected during car journeys already makes it possible to avoid traffic jams or to know about the need to organize a carpool. Another example: in the near future, the maintenance interventions to be carried out on the road network will be planned with data collected using gyroscopes that detect potholes. The application domains are therefore numerous, as are the prob- lems associated with them. The articles that make up this thesis deal with systems that share two key characteristics: a spatio-temporal context and a decentralized architec- ture. In addition, the systems described in these articles revolve around three temporal perspectives: the present, the past, and the future. Systems associated with the present perspective enable a very large number of connected objects to communicate in near real-time, according to a spatial context. Our contributions in this area enable this type of decentralized system to be scaled-out on commodity hardware, i.e., to adapt as the volume of data that arrives in the system increases. Systems associated with the past perspective, often referred to as trajectory indexes, are intended for the access to the large volume of spatio-temporal data collected by connected objects. Our contributions in this area makes it possible to handle particularly dense trajectory datasets, a problem that has not been addressed previously. Finally, systems associated with the future per- spective rely on past trajectories to predict the trajectories that the connected objects will follow. Our contributions predict the trajectories followed by connected objects with a previously unmet granularity. Although involving different domains, these con- tributions are structured around the common denominators of the underlying systems, which opens the possibility of being able to deal with these problems more generically in the near future

    An integrative framework for cooperative production resources in smart manufacturing

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    Under the push of Industry 4.0 paradigm modern manufacturing companies are dealing with a significant digital transition, with the aim to better address the challenges posed by the growing complexity of globalized businesses (Hermann, Pentek, & Otto, Design principles for industrie 4.0 scenarios, 2016). One basic principle of this paradigm is that products, machines, systems and business are always connected to create an intelligent network along the entire factory\u2019s value chain. According to this vision, manufacturing resources are being transformed from monolithic entities into distributed components, which are loosely coupled and autonomous but nevertheless provided of the networking and connectivity capabilities enabled by the increasingly widespread Industrial Internet of Things technology. Under these conditions, they become capable of working together in a reliable and predictable manner, collaborating among themselves in a highly efficient way. Such a mechanism of synergistic collaboration is crucial for the correct evolution of any organization ranging from a multi-cellular organism to a complex modern manufacturing system (Moghaddam & Nof, 2017). Specifically of the last scenario, which is the field of our study, collaboration enables involved resources to exchange relevant information about the evolution of their context. These information can be in turn elaborated to make some decisions, and trigger some actions. In this way connected resources can modify their structure and configuration in response to specific business or operational variations (Alexopoulos, Makris, Xanthakis, Sipsas, & Chryssolouris, 2016). Such a model of \u201csocial\u201d and context-aware resources can contribute to the realization of a highly flexible, robust and responsive manufacturing system, which is an objective particularly relevant in the modern factories, as its inclusion in the scope of the priority research lines for the H2020 three-year period 2018-2020 can demonstrate (EFFRA, 2016). Interesting examples of these resources are self-organized logistics which can react to unexpected changes occurred in production or machines capable to predict failures on the basis of the contextual information and then trigger adjustments processes autonomously. This vision of collaborative and cooperative resources can be realized with the support of several studies in various fields ranging from information and communication technologies to artificial intelligence. An update state of the art highlights significant recent achievements that have been making these resources more intelligent and closer to the user needs. However, we are still far from an overall implementation of the vision, which is hindered by three major issues. The first one is the limited capability of a large part of the resources distributed within the shop floor to automatically interpret the exchanged information in a meaningful manner (semantic interoperability) (Atzori, Iera, & Morabito, 2010). This issue is mainly due to the high heterogeneity of data model formats adopted by the different resources used within the shop floor (Modoni, Doukas, Terkaj, Sacco, & Mourtzis, 2016). Another open issue is the lack of efficient methods to fully virtualize the physical resources (Rosen, von Wichert, Lo, & Bettenhausen, 2015), since only pairing physical resource with its digital counterpart that abstracts the complexity of the real world, it is possible to augment communication and collaboration capabilities of the physical component. The third issue is a side effect of the ongoing technological ICT evolutions affecting all the manufacturing companies and consists in the continuous growth of the number of threats and vulnerabilities, which can both jeopardize the cybersecurity of the overall manufacturing system (Wells, Camelio, Williams, & White, 2014). For this reason, aspects related with cyber-security should be considered at the early stage of the design of any ICT solution, in order to prevent potential threats and vulnerabilities. All three of the above mentioned open issues have been addressed in this research work with the aim to explore and identify a precise, secure and efficient model of collaboration among the production resources distributed within the shop floor. This document illustrates main outcomes of the research, focusing mainly on the Virtual Integrative Manufacturing Framework for resources Interaction (VICKI), a potential reference architecture for a middleware application enabling semantic-based cooperation among manufacturing resources. Specifically, this framework provides a technological and service-oriented infrastructure offering an event-driven mechanism that dynamically propagates the changing factors to the interested devices. The proposed system supports the coexistence and combination of physical components and their virtual counterparts in a network of interacting collaborative elements in constant connection, thus allowing to bring back the manufacturing system to a cooperative Cyber-physical Production System (CPPS) (Monostori, 2014). Within this network, the information coming from the productive chain can be promptly and seamlessly shared, distributed and understood by any actor operating in such a context. In order to overcome the problem of the limited interoperability among the connected resources, the framework leverages a common data model based on the Semantic Web technologies (SWT) (Berners-Lee, Hendler, & Lassila, 2001). The model provides a shared understanding on the vocabulary adopted by the distributed resources during their knowledge exchange. In this way, this model allows to integrate heterogeneous data streams into a coherent semantically enriched scheme that represents the evolution of the factory objects, their context and their smart reactions to all kind of situations. The semantic model is also machine-interpretable and re-usable. In addition to modeling, the virtualization of the overall manufacturing system is empowered by the adoption of an agent-based modeling, which contributes to hide and abstract the control functions complexity of the cooperating entities, thus providing the foundations to achieve a flexible and reconfigurable system. Finally, in order to mitigate the risk of internal and external attacks against the proposed infrastructure, it is explored the potential of a strategy based on the analysis and assessment of the manufacturing systems cyber-security aspects integrated into the context of the organization\u2019s business model. To test and validate the proposed framework, a demonstration scenarios has been identified, which are thought to represent different significant case studies of the factory\u2019s life cycle. To prove the correctness of the approach, the validation of an instance of the framework is carried out within a real case study. Moreover, as for data intensive systems such as the manufacturing system, the quality of service (QoS) requirements in terms of latency, efficiency, and scalability are stringent, an evaluation of these requirements is needed in a real case study by means of a defined benchmark, thus showing the impact of the data storage, of the connected resources and of their requests

    NoSQL Data Stores In Publish/Subscribe-Based RESTful Web Services

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    In the era of mobile cloud computing, the consumption of virtualized software and Web-based services from super-back-end infrastructure using smartphones and tablets is gaining much research attention from both the industry and academia. Nowadays, these mobile devices generate and access multimedia data hosted in social media and other sources in order to enhance the users’ multimedia experience. However, multimedia data is unstructured which can lead to challenges with data synchronization between these mobile devices and the cloud computing back-end. The issue with data synchronization is further fueled by the fact that mobile devices can experience intermittent connectivity losses due to unstable wireless bandwidths. While previous works proposed Simple Object Access Protocol (SOAP) -based middleware for the Web services’ synchronization, this approach is not efficient in a mobile environment because the SOAP protocol is verbose. Thus, the Representational State Transfer (REST) standard has been proposed recently to model the Web services since it is lightweight. This thesis proposes a novel approach for implementing a REST-based mobile Web Service for multimedia file sharing that utilizes a channel-based publish/subscribe communication scheme to synchronize smartphone or tablet-hosted NoSQL databases with a cloud-hosted NoSQL database. This thesis evaluates the synchronicity and the scalability of a prototype system that was implemented according to this approach. Also, this thesis assesses the overhead of the middleware component of the system
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