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.

Automated summary

This book provides a comprehensive discussion on energy efficient computation offloading and resource management in mobile edge computing (MEC), offering valuable insights for practical applications of MEC and inspiring new ideas for future MEC-enabled IoT networks.