书目名称 | Energy Efficient Computation Offloading in Mobile Edge Computing |
编辑 | Ying Chen,Ning Zhang,Sherman Shen |
视频video | |
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 |
丛书名称 | Wireless Networks |
图书封面 |  |
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 |
关键词 | Mobile Edge Computing; Internet Of Things; computation offloading; task scheduling; energy efficiency; dy |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-031-16822-2 |
isbn_softcover | 978-3-031-16824-6 |
isbn_ebook | 978-3-031-16822-2Series ISSN 2366-1186 Series E-ISSN 2366-1445 |
issn_series | 2366-1186 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |