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Managing Computing Infrastructure for IoT Data

机译:管理物联网数据的计算基础架构

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Digital data have become a torrent engulfing every area of business, science and engineering disciplines, gushing into every economy, every organization and every user of digital technology. In the age of big data, deriving values and insights from big data using rich analytics becomes important for achieving competitiveness, success and leadership in every field. The Internet of Things (IoT) is causing the number and types of products to emit data at an unprecedented rate. Heterogeneity, scale, timeliness, complexity, and privacy problems with large data impede progress at all phases of the pipeline that can create value from data issues. With the push of such massive data, we are entering a new era of computing driven by novel and ground breaking research innovation on elastic parallelism, partitioning and scalability. Designing a scalable system for analysing, processing and mining huge real world datasets has become one of the challenging problems facing both systems researchers and data management researchers. In this paper, we will give an overview of computing infrastructure for IoT data processing, focusing on architectural and major challenges of massive data. We will briefly discuss about emerging computing infrastructure and technologies that are promising for improving massive data management.
机译:数字数据已经席卷了商业,科学和工程学科的各个领域,涌入了每个经济体,每个组织和每个数字技术用户。在大数据时代,使用丰富的分析从大数据中获得价值和见解对于在各个领域实现竞争力,成功和领导地位至关重要。物联网(IoT)导致产品的数量和类型以前所未有的速度发射数据。大数据的异构性,规模,及时性,复杂性和隐私性问题阻碍了管道的各个阶段的进展,这些阶段可以从数据问题中创造价值。随着海量数据的推动,我们正在进入一个新的计算时代,这是有关弹性并行性,分区和可伸缩性的新颖且突破性的研究创新所驱动的。设计用于分析,处理和挖掘巨大的现实世界数据集的可伸缩系统已经成为系统研究人员和数据管理研究人员面临的挑战性问题之一。在本文中,我们将概述用于物联网数据处理的计算基础架构,重点关注海量数据的体系结构和主要挑战。我们将简要讨论有关有望改善海量数据管理的新兴计算基础架构和技术。

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