Artificial Intelligence for Edge Computing
За е-книгава
The book is broken down into three parts: core problems, distributed problems, and other cross-cutting issues. It explores the challenges arising in Edge AI contexts. Some of these challenges (such as neural network model reduction to fit resource-constrained hardware) are unique to the edge environment. They need a novel category of solutions that do not parallel more typical concerns in mainstream AI. Others are adaptations of mainstream AI challenges to the edge space. An example is overcoming the cost of data labeling. The labeling problem is pervasive, but its solution in the IoT application context is different from other contexts. This book is not a survey of the state of the art. With thousands of publications appearing in AI every year, such a survey is doomed to be incomplete on arrival. It is also not a comprehensive coverage of all the problems in the space of Edge AI. Different applications pose different challenges, and a more comprehensive coverage should be more application specific. Instead, this book covers some of the more endemic challenges across the range of IoT/CPS applications. To offer coverage in some depth, we opt to cover mainly one or a few representative solutions for each of these endemic challenges in sufficient detail, rather that broadly touching on all relevant prior work. The underlying philosophy is one of illustrating by example. The solutions are curated to offer insight into a way of thinking that characterizes Edge AI research and distinguishes its solutions from their more mainstream counterparts.
За авторот
Tarek Abdelzaher received his Ph.D. degree in Computer Science and Engineering from the University of Michigan in 1999. He is presently a Sohaib and Sara Abbasi Professor of Computer Science and a Willett Faculty Scholar at the University of Illinois. Abdelzaher has over 300 refereed publications in Real-time Computing, Distributed Systems, Sensor Networks, and IoT, with more than 41,000 citations according to Google Scholar, and an H-index of 96. He served as Editor-in-Chief of the Journal of Real-Time Systems for many years, and as an Associate Editor of multiple journals including IEEE TMC, IEEE TPDS, ACM ToSN, ACM TIoT, and ACM ToIT. He also chaired several top conferences in his field, including RTSS, Sensys, Infocom, ICDCS, IPSN, RTAS, DCoSS, EWSN, IWQoS, and ICAC. Abdelzaher received the IEEE Outstanding Technical Achievement and Leadership Award in Real-time Systems (2012), a Xerox Research Award (2011), and over a dozen best paper awards. He is a fellow of IEEE and ACM.
Ting He received the Ph.D. degree in Electrical and Computer Engineering from Cornell University. Dr. He is an Associate Professor in the School of Electrical Engineering and Computer Science at the Pennsylvania State University, University Park, PA. Her interests reside at the intersection of computer networking, distributed computing, and machine learning. Dr. He is a Senior Member of IEEE. She has served as Associate Editor for IEEE Transactions on Communications and IEEE/ACM Transactions on Networking, General Co-Chair of IEEE RTCSA, TPC Co-Chair of IEEE ICCCN, Area TPC Chair of IEEE INFOCOM, and TPC member of many international conferences on networking and distributed computing. She received multiple awards from IBM and International Technology Alliance (ITA) for technical contributions, and multiple best paper awards from IEEE Communications Society, IEEE ICDCS, ACM SIGMETRICS, and IEEE ICASSP.
