A cloud robotics architecture for an emergency management and monitoring service in a smart cityenvironment

Cloud robotics is revolutionizing not only the robotics industry but also the ICT world, giving robots more storage and computing capacity, opening new scenarios that blend the physical to the digital world. In this vision new IT architectures are required to manage robots, retrieve data from them and create services to interact with users. In this paper a possible implementation of a cloud robotics architecture for the interaction between users and UAVs is described. Using the latter as monitoring agents, a service for fighting crime in urban environment is proposed, making one step forward towards the idea of smart cit

Authentication and authorisation in entrusted unions

This paper reports on the status of a project whose aim is to implement and demonstrate in a real-life environment an integrated eAuthentication and eAuthorisation framework to enable trusted collaborations and delivery of services across different organisational/governmental jurisdictions. This aim will be achieved by designing a framework with assurance of claims, trust indicators, policy enforcement mechanisms and processing under encryption to address the security and confidentiality requirements of large distributed infrastructures. The framework supports collaborative secure distributed storage, secure data processing and management in both the cloud and offline scenarios and is intended to be deployed and tested in two pilot studies in two different domains, viz, Bio-security incident management and Ambient Assisted Living (eHealth). Interim results in terms of security requirements, privacy preserving authentication, and authorisation are reported

Architectural design of experience based factory model for software development process in cloud computing: integration with workflow and multi-agent system

A model which is based on experience factory approach has been proposed earlier, calledEBF-SD, to overcome the limitations of experience management in software developmentdomain. An application prototype, which is then called SDeX, is developed based on theproposed model. The study on correlation analysis indicates that automation do have positiverelationship with other components: knowledge management, cloud, collaboration and portal.This paper further discusses the high level prototype development with the emphasis on thearchitectural design. Automation features are incorporated in the design in which workflowsystem and intelligent agents are integrated, and the facilitation of cloud environment isempowered to further support the automation.Keywords: architectural design; knowledge management; experience factory; workflow;multi-agent system; cloud automation

Enabling stream processing for people-centric IoT based on the fog computing paradigm

The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture

funcX: A Federated Function Serving Fabric for Science

Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approaches must enable computation to be mobile, so that, for example, it can occur near data, be triggered by events (e.g., arrival of new data), be offloaded to specialized accelerators, or run remotely where resources are available. They also require new design approaches in which monolithic applications can be decomposed into smaller components, that may in turn be executed separately and on the most suitable resources. To address these needs we present funcX---a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. funcX's endpoint software can transform existing clouds, clusters, and supercomputers into function serving systems, while funcX's cloud-hosted service provides transparent, secure, and reliable function execution across a federated ecosystem of endpoints. We motivate the need for funcX with several scientific case studies, present our prototype design and implementation, show optimizations that deliver throughput in excess of 1 million functions per second, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than more than 130000 concurrent workers.Comment: Accepted to ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020). arXiv admin note: substantial text overlap with arXiv:1908.0490

An integrative framework for cooperative production resources in smart manufacturing

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