You are cordially invited to the talk delivered by Dr. Meixia Tao from 10:30 am to 11:30 am on November 8, 2019.
Computation Replication for Mobile Edge Computing
Meixia Tao is a Professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. She received the Ph.D. degree in electrical and electronic engineering from Hong Kong University of Science and Technology in 2003. Her current research interests include wireless caching, edge computing, physical layer multicasting, and resource allocation.
Dr. Tao served as a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications. She was on the Editorial Board of the IEEE Transactions on Wireless Communications (2007-2011), and the IEEE Transactions on Communications (2012-2018), the IEEE Communications Letters (2009-2012), and the IEEE Wireless Communications Letters (2011-2015). She has also served as Symposium Oversight Chair of IEEE ICC 2019, Symposium Co-Chair of IEEE GLOBECOM 2018, the TPC chair of IEEE/CIC ICCC 2014 and Symposium Co-Chair of IEEE ICC 2015.
Dr. Tao is a Fellow of IEEE. She is the recipient of the IEEE Marconi Prize Paper Award in 2019, the IEEE Heinrich Hertz Award for Best Communications Letters in 2013, the IEEE/CIC International Conference on Communications in China (ICCC) Best Paper Award in 2015, and the International Conference on Wireless Communications and Signal Processing (WCSP) Best Paper Award in 2012.
Time & Date
10:30 am – 11:30 am, November 8 (Friday), 2019
Room 208, Cheng Dao Building
Existing works on task offloading in mobile edge computing (MEC) networks often assume a task be executed once at a single edge node (EN). Downloading the computed result from the EN back to the mobile user thus may suffer long delay if the downlink channel experiences strong interference or deep fading. In this talk, we shall exploit the idea of computation replication in MEC networks to speed up the downloading phase. Computation replication allows each user to offload its task to multiple ENs for repetitive execution so as to create multiple copies of the computed result at different ENs which can then enable transmission cooperation and hence reduce the communication latency for result downloading. Yet, computation replication may also increase the communication latency for task uploading. The aim of this talk is to characterize asymptotically an order-optimal upload-download communication latency pair for a given computation load in a multi-user multi-server MEC network. Several insights on the fundamental computation-communication tradeoffs will be revealed.
All of you are warmly welcomed.