252 research outputs found

    Next Generation Cloud Computing: New Trends and Research Directions

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    The landscape of cloud computing has significantly changed over the last decade. Not only have more providers and service offerings crowded the space, but also cloud infrastructure that was traditionally limited to single provider data centers is now evolving. In this paper, we firstly discuss the changing cloud infrastructure and consider the use of infrastructure from multiple providers and the benefit of decentralising computing away from data centers. These trends have resulted in the need for a variety of new computing architectures that will be offered by future cloud infrastructure. These architectures are anticipated to impact areas, such as connecting people and devices, data-intensive computing, the service space and self-learning systems. Finally, we lay out a roadmap of challenges that will need to be addressed for realising the potential of next generation cloud systems.Comment: Accepted to Future Generation Computer Systems, 07 September 201

    Addressing the Security Gap in IoT: Towards an IoT Cyber Range.

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    The paradigm of Internet of Things has now reached a maturity level where the pertinent research goal is the successful application of IoT technologies in systems of high technological readiness level. However, while basic aspects of IoT connectivity and networking have been well studied and adequately addressed, this has not been the case for cyber security aspects of IoT. This is nicely demonstrated by the number of IoT testbeds focusing on networking aspects and the lack of IoT testbeds focusing on security aspects. Towards addressing the existing and growing skills-shortage in IoT cyber security, we present an IoT Cyber Range (IoT-CR); an IoT testbed designed for research and training in IoT security. The IoT-CR allows the user to specify and work on customisable IoT networks, both virtual and physical, and supports the concurrent execution of multiple scenarios in a scalable way following a modular architecture. We first provide an overview of existing, state of the art IoT testbeds and cyber security related initiatives. We then present the design and architecture of the IoT Cyber Range, also detailing the corresponding RESTful APIs that help de-associate the IoT-CR tiers and obfuscate underlying complexities. The design is focused around the end-user and is based on the four design principles for Cyber Range development discussed in the introduction. Finally, we demonstrate the use of the facility via a red/blue team scenario involving a variant of man-in-the-middle attack using IoT devices. Future work includes the use of the IoT-CR by cohorts of trainees in order to evaluate the effectiveness of specific scenarios in acquiring IoT-related cyber-security knowledge and skills, as well as the IoT-CR integration with a pan-European cyber-security competence network

    End-to-end slices to orchestrate resources and services in the cloud-to-edge continuum

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    Fog computing, combined with traditional cloud computing, offers an inherently distributed infrastructure – referred to as the cloud-to-edge continuum – that can be used for the execution of low-latency and location-aware IoT services. The management of such an infrastructure is complex: resources in multiple domains need to be accessed by several tenants, while an adequate level of isolation and performance has to be guaranteed. This paper proposes the dynamic allocation of end-to-end slices to perform the orchestration of resources and services in such a scenario. These end-to-end slices require a unified resource management approach that encompasses both data centre and network resources. Currently, fog orchestration is mainly focused on the management of compute resources, likewise, the slicing domain is specifically centred solely on the creation of isolated network partitions. A unified resource orchestration strategy, able to integrate the selection, configuration and management of compute and network resources, as part of a single abstracted object, is missing. This work aims to minimise the silo-effect, and proposes end-to-end slices as the foundation for the comprehensive orchestration of compute resources, network resources, and services in the cloud-to-edge continuum, as well acting as the basis for a system implementation. The concept of the end-to-end slice is formally described via a graph-based model that allows for dynamic resource discovery, selection and mapping via different algorithms and optimisation goals; and a working system is presented as the way to build slices across multiple domains dynamically, based on that model. These are independently accessible objects that abstract resources of various providers – traded via a Marketplace – with compute slices, allocated using the bare-metal cloud approach, being interconnected to each other via the connectivity of network slices. Experiments, carried out on a real testbed, demonstrate three features of the end-to-end slices: resources can be selected, allocated and controlled in a softwarised fashion; tenants can instantiate distributed IoT services on those resources transparently; the performance of a service is absolutely not affected by the status of other slices that share the same resource infrastructure

    End-to-end slices to orchestrate resources and services in the cloud-to-edge continuum

    Get PDF
    Fog computing, combined with traditional cloud computing, offers an inherently distributed infrastructure – referred to as the cloud-to-edge continuum – that can be used for the execution of low-latency and location-aware IoT services. The management of such an infrastructure is complex: resources in multiple domains need to be accessed by several tenants, while an adequate level of isolation and performance has to be guaranteed. This paper proposes the dynamic allocation of end-to-end slices to perform the orchestration of resources and services in such a scenario. These end-to-end slices require a unified resource management approach that encompasses both data centre and network resources. Currently, fog orchestration is mainly focussed on the management of compute resources, likewise, the slicing domain is specifically centred solely on the creation of isolated network partitions. A unified resource orchestration strategy, able to integrate the selection, configuration and management of compute and network resources, as part of a single abstracted object, is missing. This work aims to minimise the silo-effect, and proposes end-to-end slices as the foundation for the comprehensive orchestration of compute resources, network resources, and services in the cloud-to-edge continuum, as well acting as the basis for a system implementation. The concept of the end-to-end slice is formally described via a graph-based model that allows for dynamic resource discovery, selection and mapping via different algorithms and optimisation goals; and a working system is presented as the way to build slices across multiple domains dynamically, based on that model. These are independently accessible objects that abstract resources of various providers – traded via a Marketplace – with compute slices, allocated using the bare-metal cloud approach, being interconnected to each other via the connectivity of network slices. Experiments, carried out on a real testbed, demonstrate three features of the end-to-end slices: resources can be selected, allocated and controlled in a softwarised fashion; tenants can instantiate distributed IoT services on those resources transparently; the performance of a service is absolutely not affected by the status of other slices that share the same resource infrastructure

    Monitoring in fog computing: state-of-the-art and research challenges

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    Fog computing has rapidly become a widely accepted computing paradigm to mitigate cloud computing-based infrastructure limitations such as scarcity of bandwidth, large latency, security, and privacy issues. Fog computing resources and applications dynamically vary at run-time, and they are highly distributed, mobile, and appear-disappear rapidly at any time over the internet. Therefore, to ensure the quality of service and experience for end-users, it is necessary to comply with a comprehensive monitoring approach. However, the volatility and dynamism characteristics of fog resources make the monitoring design complex and cumbersome. The aim of this article is therefore three-fold: 1) to analyse fog computing-based infrastructures and existing monitoring solutions; 2) to highlight the main requirements and challenges based on a taxonomy; 3) to identify open issues and potential future research directions.This work has been (partially) funded by H2020 EU/TW 5G-DIVE (Grant 859881) and H2020 5Growth (Grant 856709). It has been also funded by the Spanish State Research Agency (TRUE5G project, PID2019-108713RB-C52 PID2019-108713RB-C52 / AEI / 10.13039/501100011033)

    The Cloud-to-Thing Continuum

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    The Internet of Things offers massive societal and economic opportunities while at the same time significant challenges, not least the delivery and management of the technical infrastructure underpinning it, the deluge of data generated from it, ensuring privacy and security, and capturing value from it. This Open Access Pivot explores these challenges, presenting the state of the art and future directions for research but also frameworks for making sense of this complex area. This book provides a variety of perspectives on how technology innovations such as fog, edge and dew computing, 5G networks, and distributed intelligence are making us rethink conventional cloud computing to support the Internet of Things. Much of this book focuses on technical aspects of the Internet of Things, however, clear methodologies for mapping the business value of the Internet of Things are still missing. We provide a value mapping framework for the Internet of Things to address this gap. While there is much hype about the Internet of Things, we have yet to reach the tipping point. As such, this book provides a timely entrée for higher education educators, researchers and students, industry and policy makers on the technologies that promise to reshape how society interacts and operates

    Probabilistic QoS-aware Placement of VNF chains at the Edge

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    Deploying IoT-enabled Virtual Network Function (VNF) chains to Cloud-Edge infrastructures requires determining a placement for each VNF that satisfies all set deployment requirements as well as a software-defined routing of traffic flows between consecutive functions that meets all set communication requirements. In this article, we present a declarative solution, EdgeUsher, to the problem of how to best place VNF chains to Cloud-Edge infrastructures. EdgeUsher can determine all eligible placements for a set of VNF chains to a Cloud-Edge infrastructure so to satisfy all of their hardware, IoT, security, bandwidth, and latency requirements. It exploits probability distributions to model the dynamic variations in the available Cloud-Edge infrastructure, and to assess output eligible placements against those variations
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