63,887 research outputs found

    Leveraging Kubernetes in Edge-Native Cable Access Convergence

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    Public clouds provide infrastructure services and deployment frameworks for modern cloud-native applications. As the cloud-native paradigm has matured, containerization, orchestration and Kubernetes have become its fundamental building blocks. For the next step of cloud-native, an interest to extend it to the edge computing is emerging. Primary reasons for this are low-latency use cases and the desire to have uniformity in cloud-edge continuum. Cable access networks as specialized type of edge networks are not exception here. As the cable industry transitions to distributed architectures and plans the next steps to virtualize its on-premise network functions, there are opportunities to achieve synergy advantages from convergence of access technologies and services. Distributed cable networks deploy resource-constrained devices like RPDs and RMDs deep in the edge networks. These devices can be redesigned to support more than one access technology and to provide computing services for other edge tenants with MEC-like architectures. Both of these cases benefit from virtualization. It is here where cable access convergence and cloud-native transition to edge-native intersect. However, adapting cloud-native in the edge presents a challenge, since cloud-native container runtimes and native Kubernetes are not optimal solutions in diverse edge environments. Therefore, this thesis takes as its goal to describe current landscape of lightweight cloud-native runtimes and tools targeting the edge. While edge-native as a concept is taking its first steps, tools like KubeEdge, K3s and Virtual Kubelet can be seen as the most mature reference projects for edge-compatible solution types. Furthermore, as the container runtimes are not yet fully edge-ready, WebAssembly seems like a promising alternative runtime for lightweight, portable and secure Kubernetes compatible workloads

    The troubled journey of QoS: From ATM to content networking, edge-computing and distributed internet governance

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    Network Quality of Service (QoS) and the associated user Quality of Experience (QoE) have always been the networking “holy grail” and have been sought after through various different approaches and networking technologies over the last decades. Despite substantial amounts of effort invested in the area, there has been very little actual deployment of mechanisms to guarantee QoS in the Internet. As a result, the Internet is largely operating on a “best effort” basis in terms of QoS. Here, we attempt a historical overview in order to better understand how we got to the point where we are today and consider the evolution of QoS/QoE in the future. As we move towards more demanding networking environments where enormous amounts of data is produced at the edge of the network (e.g., from IoT devices), computation will also need to migrate to the edge in order to guarantee QoS. In turn, we argue that distributed computing at the edge of the network will inevitably require infrastructure decentralisation. That said, trust to the infrastructure provider is more difficult to guarantee and new components need to be incorporated into the Internet landscape in order to be able to support emerging applications, but also achieve acceptable service quality. We start from the first steps of ATM and related IP-based technologies, we consider recent proposals for content-oriented and Information-Centric Networking, mobile edge and fog computing, and finally we see how distributed Internet governance through Distributed Ledger Technology and blockchains can influence QoS in future networks

    A gap analysis of Internet-of-Things platforms

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    We are experiencing an abundance of Internet-of-Things (IoT) middleware solutions that provide connectivity for sensors and actuators to the Internet. To gain a widespread adoption, these middleware solutions, referred to as platforms, have to meet the expectations of different players in the IoT ecosystem, including device providers, application developers, and end-users, among others. In this article, we evaluate a representative sample of these platforms, both proprietary and open-source, on the basis of their ability to meet the expectations of different IoT users. The evaluation is thus more focused on how ready and usable these platforms are for IoT ecosystem players, rather than on the peculiarities of the underlying technological layers. The evaluation is carried out as a gap analysis of the current IoT landscape with respect to (i) the support for heterogeneous sensing and actuating technologies, (ii) the data ownership and its implications for security and privacy, (iii) data processing and data sharing capabilities, (iv) the support offered to application developers, (v) the completeness of an IoT ecosystem, and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims to highlight the deficiencies of today's solutions to improve their integration to tomorrow's ecosystems. In order to strengthen the finding of our analysis, we conducted a survey among the partners of the Finnish IoT program, counting over 350 experts, to evaluate the most critical issues for the development of future IoT platforms. Based on the results of our analysis and our survey, we conclude this article with a list of recommendations for extending these IoT platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer Communications, special issue on the Internet of Things: Research challenges and solution

    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

    The cybercultural moment and the new media field

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    This article draws on Pierre Bourdieu’s field theory to understand the regenerative “belief in the new” in new media culture and web history. I begin by noting that discursive constructions of the web as disruptive, open, and participatory have emerged at various points in the medium’s history, and that these discourses are not as neatly tied to economic interests as most new media criticism would suggest. With this in mind, field theory is introduced as a potential framework for understanding this (re)production of a belief in the new as a dynamic of the interplay of cultural and symbolic forms of capital within the new media field. After discussing how Bourdieu’s theory might be applied to new media culture in general terms, I turn to a key moment in the emergence of the new media field—the rise of cybercultural magazines Mondo 2000 and Wired in the early 1990s—to illustrate how Bourdieu’s theory may be adapted in the study of new media history

    Research and Education in Computational Science and Engineering

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    Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

    Analytical Challenges in Modern Tax Administration: A Brief History of Analytics at the IRS

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    Host-pathogen evolutionary signatures reveal dynamics and future invasions of vampire bat rabies

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    Anticipating how epidemics will spread across landscapes requires understanding host dispersal events that are notoriously difficult to measure. Here, we contrast host and virus genetic signatures to resolve the spatiotemporal dynamics underlying geographic expansions of vampire bat rabies virus (VBRV) in Peru. Phylogenetic analysis revealed recent viral spread between populations that, according to extreme geographic structure in maternally inherited host mitochondrial DNA, appeared completely isolated. In contrast, greater population connectivity in biparentally inherited nuclear microsatellites explained the historical limits of invasions, suggesting that dispersing male bats spread VBRV between genetically isolated female populations. Host nuclear DNA further indicated unanticipated gene flow through the Andes mountains connecting the VBRV-free Pacific coast to the VBRV-endemic Amazon rainforest. By combining Bayesian phylogeography with landscape resistance models, we projected invasion routes through northern Peru that were validated by real-time livestock rabies mortality data. The first outbreaks of VBRV on the Pacific coast of South America could occur by June 2020, which would have serious implications for agriculture, wildlife conservation, and human health. Our results show that combining host and pathogen genetic data can identify sex biases in pathogen spatial spread, which may be a widespread but underappreciated phenomenon, and demonstrate that genetic forecasting can aid preparedness for impending viral invasions
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