Energy efficient computation offloading in mobile edge computing

Energy efficient computation offloading in mobile edge computing

by Chen, Ying

Type Book
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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 consump…

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Title Statements

  • Full title :Energy efficient computation offloading in mobile edge computing / Ying Chen, Ning Zhang, Yuan Wu, Sherman Shen.

Summary

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.

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Edition Statements

  • Publication Date:2022.

Publication Statements

  • Publisher(s):Springer
  • Place of Publication:Cham
  • Language:eng
  • Publication Date:2022.

The Physical Object

  • Description:1 online resource : : illustrations (black and white).

Edition Identifiers

  • ISBN:9783031168222, 3031168224
  • DOI:10.1007/978-3-031-16822-2
  • oclc:on1350381178
  • LC Classification:QA76.583
  • Dewey Decimal:005.25

Table of Contents

Introduction -- 1.1 Background -- 1.1.1 Mobile Cloud Computing -- 1.1.2 Mobile Edge Computing -- 1.1.3 Computation Offloading -- 1.2 Challenges -- 1.3 Contributions -- 1.4 Book Outline -- References -- 2 Dynamic Computation Offloading for Energy Efficiency in Mobile -- Edge Computing -- 2.1 System Model and Problem Statement -- 2.1.1 Network Model -- 2.1.2 Task Offloading Model -- 2.1.3 Task Queuing Model -- 2.1.4 Energy Consumption Model -- 2.1.5 Problem Statement -- 2.2 EEDCO: Energy Efficient Dynamic Computing Offloading for -- Mobile Edge Computing -- 2.2.1 Joint Optimization of Energy and Queue -- 2.2.2 Dynamic Computation Offloading for Mobile Edge -- Computing -- 2.2.3 Trade-off Between Queue Backlog and Energy Efficiency -- 2.2.4 Convergence and Complexity Analysis -- 2.3 Performance Evaluation -- 2.3.1 Impacts of Parameters -- 2.3.2 Performance Comparison with EA and QW Schemes -- 2.4 Literature Review -- 2.5 Summary -- References -- ix -- x Contents -- 3 Energy Efficient Offloading and Frequency Scaling for Internet of -- Things Devices -- 3.1 System Model and Problem Formulation -- 3.1.1 Network Model -- 3.1.2 Task Model -- 3.1.3 Queuing Model -- 3.1.4 Energy Consumptio…

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Subjects

Edge computing Edge computing -- Energy consumption Mobile computing Mobile computing -- Energy consumption

Writers

Chen, Ying Shen, X., (Xuemin) Wu, Yuan Zhang, Ning, (Computer scientist)

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