21 research outputs found

    PLAY: Semantics-based Event Marketplace

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    International audienceIn this paper we present PLAY Platform, a Web-oriented distributed semantic middleware that serves as an Event M arketplace: the place where heterogeneous events can be integrated and combined. The purpose of the platform is to derive useful information from diverse real-time sources such as collaborative processes. The platform provides technology where instant results are needed or where heterogeneous data must be integrated on the fly or where the data arrive fast enough to require the stream processing nature of our approach. The main advantages of the platforms are its scalability (cloud-based nature) and the expressivity of the event combinations that can be defined (using both real-time and historical data). The platform has been applied in a use case about Personal data management. In this paper we present some results from the validation, focusing on smartphone and social media integration

    A survey on data storage and placement methodologies for Cloud-Big Data ecosystem

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    Abstract Currently, the data to be explored and exploited by computing systems increases at an exponential rate. The massive amount of data or so-called “Big Data” put pressure on existing technologies for providing scalable, fast and efficient support. Recent applications and the current user support from multi-domain computing, assisted in migrating from data-centric to knowledge-centric computing. However, it remains a challenge to optimally store and place or migrate such huge data sets across data centers (DCs). In particular, due to the frequent change of application and DC behaviour (i.e., resources or latencies), data access or usage patterns need to be analyzed as well. Primarily, the main objective is to find a better data storage location that improves the overall data placement cost as well as the application performance (such as throughput). In this survey paper, we are providing a state of the art overview of Cloud-centric Big Data placement together with the data storage methodologies. It is an attempt to highlight the actual correlation between these two in terms of better supporting Big Data management. Our focus is on management aspects which are seen under the prism of non-functional properties. In the end, the readers can appreciate the deep analysis of respective technologies related to the management of Big Data and be guided towards their selection in the context of satisfying their non-functional application requirements. Furthermore, challenges are supplied highlighting the current gaps in Big Data management marking down the way it needs to evolve in the near future

    An event-driven platform to manage agility

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    Context-Based, Predictive Access Control to Electronic Health Records

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    Effective access control techniques are in demand, as electronically assisted healthcare services require the patient’s sensitive health records. In emergency situations, where the patient’s well-being is jeopardized, different healthcare actors associated with emergency cases should be granted permission to access Electronic Health Records (EHRs) of patients. The research objective of our study is to develop machine learning techniques based on patients’ time sequential health metrics and integrate them with an Attribute Based Access Control (ABAC) mechanism. We propose an ABAC mechanism that can yield access to sensitive EHRs systems by applying prognostic context handlers where contextual information, is used to identify emergency conditions and permit access to medical records. Specifically, we use patients’ recent health history to predict the health metrics for the next two hours by leveraging Long Short Term Memory (LSTM) Neural Networks (NNs). These predicted health metrics values are evaluated by our personalized fuzzy context handlers, to predict the criticality of patients’ status. The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism with personalized context handlers proved to be a robust tool to enhance the performance of the access control mechanism to modern EHRs System

    Fog computing context analytics

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    A Semantic Model for Interchangeable Microservices in Cloud Continuum Computing

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    The rapid growth of new computing models that exploit the cloud continuum has a big impact on the adoption of microservices, especially in dynamic environments where the amount of workload varies over time or when Internet of Things (IoT) devices dynamically change their geographic location. In order to exploit the true potential of cloud continuum computing applications, it is essential to use a comprehensive set of various intricate technologies together. This complex blend of technologies currently raises data interoperability problems in such modern computing frameworks. Therefore, a semantic model is required to unambiguously specify notions of various concepts employed in cloud applications. The goal of the present paper is therefore twofold: (i) offering a new model, which allows an easier understanding of microservices within adaptive fog computing frameworks, and (ii) presenting the latest open standards and tools which are now widely used to implement each class defined in our proposed model

    Addressing Agility in Collaborative Processes: A comparative Study

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    7th IEEE International Conference on Digital Ecosystems and Technologies (DEST), Menlo Park, CA, JUL 24-26, 2013International audienceEfficiency of emerging digital ecosystems is strongly dependent on the efficiency of their collaborative processes. One crucial component of this efficiency is agility of collaborative processes. This article first provides a vision of agility of process in the world of workflow orchestration. Two approaches to deal with this issue (SAR from the European project PLAY and agility service from the French project SocEDA) are presented and illustrated (according to a scenario of nuclear crisis management). Comparison of both these approaches is structured according to different components of agility (detection, adaptation and reactivity). Some advantages and drawbacks of both these approaches are finally highlighted
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