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Titlebook: Energy Efficient Computation Offloading in Mobile Edge Computing; Ying Chen,Ning Zhang,Sherman Shen Book 2022 The Editor(s) (if applicable

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發(fā)表于 2025-3-21 18:36:47 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Energy Efficient Computation Offloading in Mobile Edge Computing
編輯Ying Chen,Ning Zhang,Sherman Shen
視頻videohttp://file.papertrans.cn/311/310267/310267.mp4
概述Offers a comprehensive reference book on computation offloading in Mobile Edge Computing.Presents a comprehensive review on computation offloading in MEC and energy management solutions.Provides some
叢書名稱Wireless Networks
圖書封面Titlebook: Energy Efficient Computation Offloading in Mobile Edge Computing;  Ying Chen,Ning Zhang,Sherman Shen Book 2022 The Editor(s) (if applicable
描述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 anend-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
出版日期Book 2022
關(guān)鍵詞Mobile Edge Computing; Internet Of Things; computation offloading; task scheduling; energy efficiency; dy
版次1
doihttps://doi.org/10.1007/978-3-031-16822-2
isbn_softcover978-3-031-16824-6
isbn_ebook978-3-031-16822-2Series ISSN 2366-1186 Series E-ISSN 2366-1445
issn_series 2366-1186
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Energy-Efficient Multi-Task Multi-Access Computation Offloading via NOMA,rvices in future wireless systems. This chapter leverages non-orthogonal multiple access (NOMA) for computation offloading in MA-MEC and studies a joint optimization of the multi-access multi-task computation offloading, NOMA transmission, and computation-resource allocation, with the objective of m
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2366-1186 oading in MEC and energy management solutions.Provides some 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 offloa
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Book 2022 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 compu
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978-3-031-16824-6The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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