{"title":"移动边缘计算中的节能计算卸载","authors":"B. Rong","doi":"10.1109/MWC.2023.10105148","DOIUrl":null,"url":null,"abstract":"This book provides a comprehensive introduction to energy efficient computation offloading and resource management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling, and resource scheduling. With the proliferation of mobile devices and the development of Internet of Things (IoT), more and more computation- intensive and delay-sensitive applications are running on terminal devices, which results in high-energy consumption and heavy computation load of devices. Due to the size and hardware constraints, the battery lifetime and computing capacity of terminal devices are limited. Consequently, it is hard to process all of the tasks locally while satisfying Quality of Service (QoS) requirements for devices. Mobile Edge Computing (MEC) is considered a promising paradigm that deploys computing resources at the network edge near terminal devices. With the help of MEC, terminal devices can achieve better computing performance and battery lifetime while ensuring QoS. This book discusses energy efficient computation offloading and resource allocation for MEC deeply. However, the introduction of MEC provokes challenges under energy-constrained and dynamic conditions. Therefore, it is very important to design a strategy for energy efficient computation offloading and resource allocation. To this end, this book discusses issues, such as task offloading, channel allocation, frequency scaling, and resource scheduling in MEC. The presented computation offloading and energy management solutions and the corresponding research results in this book can provide some valuable insights for practical applications of MEC and motivate new ideas for future MEC-enabled IoT networks.","PeriodicalId":13342,"journal":{"name":"IEEE Wireless Communications","volume":"30 1","pages":"8-8"},"PeriodicalIF":10.9000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy Efficient Computation Offloading in Mobile Edge Computing\",\"authors\":\"B. Rong\",\"doi\":\"10.1109/MWC.2023.10105148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This book provides a comprehensive introduction to energy efficient computation offloading and resource management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling, and resource scheduling. With the proliferation of mobile devices and the development of Internet of Things (IoT), more and more computation- intensive and delay-sensitive applications are running on terminal devices, which results in high-energy consumption and heavy computation load of devices. Due to the size and hardware constraints, the battery lifetime and computing capacity of terminal devices are limited. Consequently, it is hard to process all of the tasks locally while satisfying Quality of Service (QoS) requirements for devices. Mobile Edge Computing (MEC) is considered a promising paradigm that deploys computing resources at the network edge near terminal devices. With the help of MEC, terminal devices can achieve better computing performance and battery lifetime while ensuring QoS. This book discusses energy efficient computation offloading and resource allocation for MEC deeply. However, the introduction of MEC provokes challenges under energy-constrained and dynamic conditions. 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Energy Efficient Computation Offloading in Mobile Edge Computing
This book provides a comprehensive introduction to energy efficient computation offloading and resource management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling, and resource scheduling. With the proliferation of mobile devices and the development of Internet of Things (IoT), more and more computation- intensive and delay-sensitive applications are running on terminal devices, which results in high-energy consumption and heavy computation load of devices. Due to the size and hardware constraints, the battery lifetime and computing capacity of terminal devices are limited. Consequently, it is hard to process all of the tasks locally while satisfying Quality of Service (QoS) requirements for devices. Mobile Edge Computing (MEC) is considered a promising paradigm that deploys computing resources at the network edge near terminal devices. With the help of MEC, terminal devices can achieve better computing performance and battery lifetime while ensuring QoS. This book discusses energy efficient computation offloading and resource allocation for MEC deeply. However, the introduction of MEC provokes challenges under energy-constrained and dynamic conditions. Therefore, it is very important to design a strategy for energy efficient computation offloading and resource allocation. To this end, this book discusses issues, such as task offloading, channel allocation, frequency scaling, and resource scheduling in MEC. The presented computation offloading and energy management solutions and the corresponding research results in this book can provide some valuable insights for practical applications of MEC and motivate new ideas for future MEC-enabled IoT networks.
期刊介绍:
IEEE Wireless Communications is tailored for professionals within the communications and networking communities. It addresses technical and policy issues associated with personalized, location-independent communications across various media and protocol layers. Encompassing both wired and wireless communications, the magazine explores the intersection of computing, the mobility of individuals, communicating devices, and personalized services.
Every issue of this interdisciplinary publication presents high-quality articles delving into the revolutionary technological advances in personal, location-independent communications, and computing. IEEE Wireless Communications provides an insightful platform for individuals engaged in these dynamic fields, offering in-depth coverage of significant developments in the realm of communication technology.