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Energy-efficient dynamic traffic offloading and reconfiguration of networked data centers for big data stream mobile computing: review, challenges, and a case study

机译:用于大数据流移动计算的网络数据中心的节能动态流量卸载和重新配置:回顾,挑战和案例研究

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摘要

Big data stream mobile computing is proposed as a paradigm that relies on the convergence of broadband Internet mobile networking and real-time mobile cloud computing. It aims at fostering the rise of novel self-configuring integrated computing-communication platforms for enabling in real time the offloading and processing of big data streams acquired by resource-limited mobile/wireless devices. This position article formalizes this paradigm, discusses its most significant application opportunities, and outlines the major challenges in performing real-time energy-efficient management of the distributed resources available at both mobile devices and Internet-connected data centers. The performance analysis of a small-scale prototype is also included in order to provide insight into the energy vs. performance tradeoff that is achievable through the optimized design of the resource management modules. Performance comparisons with some state-of-the-art resource managers corroborate the discussion. Hints for future research directions conclude the article.
机译:大数据流移动计算被提出为依赖宽带互联网移动网络和实时移动云计算融合的范例。它旨在促进新型自配置集成计算通信平台的兴起,以实现实时卸载和处理资源有限的移动/无线设备获取的大数据流。这篇职位文章将这种范例形式化,讨论了其最重要的应用机会,并概述了对移动设备和与Internet连接的数据中心上可用的分布式资源执行实时节能管理的主要挑战。还包括小规模原型的性能分析,以便深入了解通过资源管理模块的优化设计可以实现的能源与性能之间的权衡。与一些最先进的资源管理器进行的性能比较证实了这一讨论。本文提供了有关未来研究方向的提示。

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