Coding for Distributed Information Systems: Adversarial Sources and Approximated Decoding

IEEE ITW 2021, Virtually from Kanazawa, Japan
Plenary Lecture

Date

Abstract

Coding is known as an effective approach to deal with some of the major challenges in distributed information systems in terms of security of the network, privacy of the data, and efficiency of the resource management. The current solutions are often based on expanding the existing coding tools and techniques, still following the conventional mindset. In this talk, we argue that there are some major scenarios and thread models that do not conform with the traditional rules. For example: (1) Coding techniques are often designed for "exact error-free decoding". However, in some scenarios, e.g. straggler-resistance computing for machine learning, only an "approximate decoding" is enough, (2) In conventional coding techniques, "input sources" are supposed to be conveyed and decoded correctly. However, in some scenarios (e.g. sharded blockchains), some parts of "input symbols" are chosen and distributed adversarially to prevent "other input symbols" from being recovered correctly. In this talk, we will review some solutions and bounds for those scenarios and discuss some open problems.

Biography
Mohammad Ali Maddah-Ali received the B.Sc. degree from Isfahan University of Technology, the M.Sc. degree from the University of Tehran, and the Ph.D. degree from the Department of Electrical and Computer Engineering, University of Waterloo, Canada in 2007. From 2007 to 2008, he was with the Wireless Technology Laboratories, Nortel Networks, Ottawa, ON, Canada. From 2008 to 2010, he was a Postdoctoral Fellow in the Department of Electrical Engineering and Computer Sciences, University of California at Berkeley. From 2010 to 2020, he was working at Bell Labs, Holmdel, NJ, as a Communication Network Research Scientist. Currently, he is a faculty member at the Department of Electrical Engineering, Sharif University of Technology. Dr. Maddah-Ali is a recipient of the IEEE International Conference on Communications (ICC) Best Paper Award in 2014, the IEEE Communications Society and IEEE Information Theory Society Joint Paper Award in 2015, and the IEEE Information Theory Society Paper Award in 2016. He is currently serving as an associate editor for the IEEE Transactions on Information Theory.