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The original idea of IS is to send two solid-gas streams to impinge
against each other at high velocity, enhancing transfer between
phases. IS is classified into two kinds: Gas-continuous impinging
streams (GIS) and Liquid-continuous ones (LIS). Impinging Streams
describes fundamentals, major properties and application of IS, as
a category of novel technologies in chemical engineering. Because
of the universality of transfer phenomena, it is receiving
widespread attention. This book represents the first book in this
area for over 10 years and covers achievements and technologies.
This book provides a comprehensive review and in-depth discussion of the state-of-the-art research literature and propose energy-efficient computation offloading and resources management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling and resource scheduling. Since the task arrival process and channel conditions are stochastic and dynamic, the authors first propose an energy efficient dynamic computing offloading scheme to minimize energy consumption and guarantee end devices' delay performance. To further improve energy efficiency combined with tail energy, the authors present a computation offloading and frequency scaling scheme to jointly deal with the stochastic task allocation and CPU-cycle frequency scaling for minimal energy consumption while guaranteeing the system stability. They also investigate delay-aware and energy-efficient computation offloading in a dynamic MEC system with multiple edge servers, and introduce an end-to-end deep reinforcement learning (DRL) approach to select the best edge server for offloading and allocate the optimal computational resource such that the expected long-term utility is maximized. Finally, the authors study the multi-task computation offloading in multi-access MEC via non-orthogonal multiple access (NOMA) and accounting for the time-varying channel conditions. An online algorithm based on DRL is proposed to efficiently learn the near-optimal offloading solutions. Researchers working in mobile edge computing, task offloading and resource management, as well as advanced level students in electrical and computer engineering, telecommunications, computer science or other related disciplines will find this book useful as a reference. Professionals working within these related fields will also benefit from this book.
This SpringerBrief offers two concrete design examples for traffic offloading. The first is an optimal resource allocation for small-cell based traffic offloading that aims at minimizing mobile users' data cost. The second is an optimal resource allocation for device-to-device assisted traffic offloading that also minimizes the total energy consumption and cellular link usage (while providing an overview of the challenging issues). Both examples illustrate the importance of proper resource allocation to the success of traffic offloading, show the consequent performance advantages of executing optimal resource allocation, and present the methodologies to achieve the corresponding optimal offloading solution for traffic offloading in heterogeneous cellular networks. The authors also include an overview of heterogeneous cellular networks and explain different traffic offloading paradigms ranging from uplink traffic offloading through small cells to downlink traffic offloading via mobile device-to-device cooperation. This brief is an excellent resource for postgraduate students studying advanced-level topics in wireless communications and networking. Researchers, engineers and professionals working in related fields will also find this brief a valuable resource tool.
This book constitutes the refereed post-conference proceedings of the 11th International Conference on Mobile Networks and Management, MONAMI 2021, held in October 2021. The conference was held virtually due to the COVID-19 pandemic. The 26 full papers were carefully reviewed and selected from 53 submissions. The papers are divided into groups of content as follows: The application of artificial intelligence for smart city; Advanced technology in edge and fog computing; Emerging technologies and applications in mobile networks and management; and Recent advances in communications and computing.
O Arquivo da Falesia Azul (Blue Cliff Record, em ingles; Biyan Lu, em chines; e em japanes, Hekiganroku) e um conjunto de 100 Koans Zen Budistas que foram compilados na China durante a dinastia Song em 1125 e depois expandido ate sua forma atual pelo mestre Zen Yuanwu Keqin (1063 - 1135). O volume tambem inclui as anotacoes e comentarios de Yuanwu sobre os 100 koans compilados por Xuedou Zhongxian (980 - 1052; 100 Versos sobre Casos Antigos). Xuedou selecionou 82 desses koans do Jingde Chuandeng Lu (Arquivo de Transmissao da Lampada da Era Jingde), e os outros ele retirou do Yunmen Guanglu (Arquivo Extenso de Yunmen Wenyan; 864 - 949). A traducao dos koans do ingles para o portugues foi realizada por Gentil Saraiva Junior, professor, escritor, editor, poeta, autor dos livros de poesia Semente de Estrelas e Canto do Amor Em Si, e tradutor da obra poetica de Walt Whitman, Folhas de Relva, para o portugues (tambem publicada no CreateSpace e KDP).
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