1,829 research outputs found

    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Design and Implementation of a Portable Framework for Application Decomposition and Deployment in Edge-Cloud Systems

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    The emergence of cyber-physical systems has brought about a significant increase in complexity and heterogeneity in the infrastructure on which these systems are deployed. One particular example of this complexity is the interplay between cloud, fog, and edge computing. However, the complexity of these systems can pose challenges when it comes to implementing self-organizing mechanisms, which are often designed to work on flat networks. Therefore, it is essential to separate the application logic from the specific deployment aspects to promote reusability and flexibility in infrastructure exploitation. To address this issue, a novel approach called "pulverization" has been proposed. This approach involves breaking down the system into smaller computational units, which can then be deployed on the available infrastructure. In this thesis, the design and implementation of a portable framework that enables the "pulverization" of cyber-physical systems are presented. The main objective of the framework is to pave the way for the deployment of cyber-physical systems in the edge-cloud continuum by reducing the complexity of the infrastructure and exploit opportunistically the heterogeneous resources available on it. Different scenarios are presented to highlight the effectiveness of the framework in different heterogeneous infrastructures and devices. Current limitations and future work are examined to identify improvement areas for the framework

    Exploring Food System Transformations in Spain (1980-2021)

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    èng In this PhD Thesis, I examine the transformations of the Spanish food system from 1980 to the present, focusing on its socioeconomic structural changes and their impacts on sustainability and social equity. My research is grounded in agrarian history and political economy approaches, and also incorporates insights from ecological and feminist economics. The first and third Chapters are empirical in nature. Based primarily on data from Spanish national accounts, the results demonstrate the increasing integration of the Spanish agri-food system into the global one and the growing dependence of agriculture on external inputs. They also reveal a sharp decline in the agrarian population along with the increase in the share of salaried work. This is explained by the reduction in the number of farms throughout the period, particularly small family farms, which also show an aging process of their holders. The decline of the agrarian income has been a major determinant in this path. The combination of these trends jeopardizes the present and future reproduction of Spanish agroecosystems. I also examine the evolution of food expenditure of Spanish households, as a first exploration of the food cost in the reproduction of labouring population. The results show a halt in the reduction of its weight, but further research is needed for a definitive conclusion. Additionally, the results suggest an increasing inequality in the distribution of value added along the agri-food chain. In the second Chapter, I develop a research framework to investigate food systems at a national level, and particularly their role in the reproduction mechanisms of the capitalist system in which they are embedded, based on the approaches of the food regimes, social metabolism, and surplus/reproduction. This framework has helped me to interpret the results from the first and third Chapters from a more comprehensive approach. The framework includes six dimensions encompassing 36 elements linked through six key cross-cutting connections

    A New Methodology to Manage FPGA Distributed Memory Content via Bitstream for Xilinx ZYNQ Devices

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    This paper proposes a methodology to access data and manage the content of distributed memories in FPGA designs through the configuration bitstream. Thanks to the methods proposed, it is possible to read and write the data content of registers without using the in/out ports of registers in a straightforward fashion. Hence, it offers the possibility of performing several operations, such as, to load, copy or compare the information stored in registers without the necessity of physical interconnections. This work includes two flows that simplify the designing process when using the proposed approach: while the first enables the protection or unprotection of writing on different partial regions through the bitstream, the second permits homogeneous instances of a design implemented in different reconfigurable regions to be obtained without losing efficiency. The approach is based and has been physically validated on the ZYNQ from Xilinx, and when using partially reconfigurable designs, it does not affect the hardware overhead nor the maximum operating frequency of the design.This work has been supported, within the fund for research groups of the Basque university system IT1440-22, by the Department of Education and, within PILAR ZE-2020/00022 and COMMUTE ZE-2021/00931 projects, by the Hazitek program, both of the Basque Government; the latter also by the Ministerio de Ciencia Innovación of Spain through the Centro para el Desarrollo Tecnológico Industrial (CDTI) within the projects IDI-20201264 and IDI-20220543, and through the Fondo Europeo de Desarrollo Regional 2014–2020 (FEDER funds)

    Investigating the Effects of Network Dynamics on Quality of Delivery Prediction and Monitoring for Video Delivery Networks

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    Video streaming over the Internet requires an optimized delivery system given the advances in network architecture, for example, Software Defined Networks. Machine Learning (ML) models have been deployed in an attempt to predict the quality of the video streams. Some of these efforts have considered the prediction of Quality of Delivery (QoD) metrics of the video stream in an effort to measure the quality of the video stream from the network perspective. In most cases, these models have either treated the ML algorithms as black-boxes or failed to capture the network dynamics of the associated video streams. This PhD investigates the effects of network dynamics in QoD prediction using ML techniques. The hypothesis that this thesis investigates is that ML techniques that model the underlying network dynamics achieve accurate QoD and video quality predictions and measurements. The thesis results demonstrate that the proposed techniques offer performance gains over approaches that fail to consider network dynamics. This thesis results highlight that adopting the correct model by modelling the dynamics of the network infrastructure is crucial to the accuracy of the ML predictions. These results are significant as they demonstrate that improved performance is achieved at no additional computational or storage cost. These techniques can help the network manager, data center operatives and video service providers take proactive and corrective actions for improved network efficiency and effectiveness

    QoS-aware architectures, technologies, and middleware for the cloud continuum

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    The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions
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