The 5G technology has been commercialized worldwide and is expected to provide superior performance with enhanced mobile broadband, ultra-low latency transmission, and massive IoT connections. Meanwhile, the edge computing paradigm gets popular to provide distributed computing and storage resources in proximity to the users. As edge services and applications prosper, 5G and edge computing will be tightly coupled and continuously promote each other forward.

Embracing this trend, however, mobile users, infrastructure providers, and service providers are all faced with the energy dilemma. On the user side, battery-powered mobile devices are much constrained by battery life, whereas mobile platforms and apps nowadays are usually power-hungry. At the infrastructure and service provider side, the energy cost of edge facilities accounts for a large proportion of operating expenses and has become a huge burden. This book provides a collection of most recent attempts to tackle the energy issues in mobile edge computing from new and promising perspectives. For example, the book investigates the pervasive low-battery anxiety among modern mobile users and quantifies the anxiety degree and likely behavior concerning the battery status. Based on the quantified model, a low-power video streaming solution is developed accordingly to save mobile devices' energy and alleviate users' low-battery anxiety. In addition to energy management for mobile users, the book also looks into potential opportunities to energy cost saving and carbon emission reduction at edge facilities, particularly the 5G base stations and geo-distributed edge datacenters.

Autorentext

Guoming Tang is a research fellow at the Peng Cheng Laboratory, Shenzhen, Guangdong, China. He received his Ph.D. degree in Computer Science from the University of Victoria, Canada, in 2017, and the Bachelor's and Master's degrees from the National University of Defense Technology, China, in 2010 and 2012, respectively. He was also a visiting research scholar of the University of Waterloo, Canada, in 2016. His research mainly focuses on green computing and computing for green.

Deke Guo received the B.S. degree in industry engineering from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 2001, and the Ph.D. degree in management science and engineering from the National University of Defense Technology, Changsha, China, in 2008. He is currently a Professor with the College of System Engineering, National University of Defense Technology, and is also with the College of Intelligence and Computing, Tianjin University. His research interests include distributed systems, software-defined networking, data center networking, wireless and mobile systems, and interconnection networks.

Kui Wu received the BSc and the MSc degrees in computer science from the Wuhan University, China, in 1990 and 1993, respectively, and the PhD degree in computing science from the University of Alberta, Canada, in 2002. He joined the Department of Computer Science, University of Victoria, Canada, in 2002, where he is currently a Full Professor. His research interests include smart grid, mobile and wireless networks, and network performance evaluation.

Inhalt

1 Introduction.- 2 Investigating Low-Battery Anxiety of Mobile Users.- 3 User Energy and LBA Aware Mobile Video Streaming.- 4 Optimal Backup Power Allocation for 5G Base Stations.- 5 Reusing Backup Batteries for Power Demand Reshaping in 5G.- 6 Software-Defined Power Supply to Geo-Distributed Edge DCs.- 7 Conclusions and Future Work.