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  • Networking for Big Data: Theory and Optimization for NDN

    Tue, Aug 22, 2017 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Edmund Yeh, Northeastern University

    Talk Title: Networking for Big Data: Theory and Optimization for NDN

    Abstract: The advent of Big Data is stimulating the development of new networking architectures which facilitate the acquisition, transmission, storage, and computation of data. In particular, Named Data Networking (NDN) is an emerging content-centric networking architecture which focuses on enabling end users to obtain the data they want, rather than to communicate with specific nodes. By naming content instead of their locations, NDN transforms data into a first-class network entity.

    In this talk, we present a new analytical and design framework for the optimization of key network functionalities within the NDN architecture, which is also broadly applicable to content delivery and peer-to-peer networks. The framework includes the joint optimization of traffic engineering and caching strategies, in order to best utilize both bandwidth and storage for efficient content distribution. It also includes optimal congestion control when user demand for content becomes excessive. We first develop distributed and adaptive algorithms for joint request forwarding and dynamic cache placement and eviction, which effectively achieve network load balancing, thereby maximizing the user demand rate that the NDN network can satisfy. Next, we investigate fair congestion control for NDN. In the absence of source-destination pairs, traditional congestion control schemes are inappropriate. Instead, we develop content-based congestion control algorithms which naturally work in concert with forwarding and caching to achieve a favorable tradeoff between the aggregate user utility from admitted content requests and the total user delay. Numerical experiments within a number of network settings demonstrate the superior performance of these algorithms in terms of multiple metrics.

    Joint work with Tracey Ho, Ying Cui, Ran Liu, Michael Burd, and Derek Leong

    Biography: Edmund Yeh received his B.S. in Electrical Engineering with Distinction and Phi Beta Kappa from Stanford University in 1994. He then studied at Cambridge University on the Winston Churchill Scholarship, obtaining his M.Phil in Engineering in 1995. He received his Ph.D. in Electrical Engineering and Computer Science from MIT under Professor Robert Gallager in 2001. He is currently Professor of Electrical and Computer Engineering at Northeastern University. He was previously Assistant and Associate Professor of Electrical Engineering, Computer Science, and Statistics at Yale University. He has held visiting positions at MIT, Stanford, Princeton, UC Berkeley, EPFL, and TU Munich.

    Professor Yeh was one of the PIs on the original NSF-funded FIA Named Data Networking project. He will serve as General Co-Chair for ACM Conference on Information Centric Networking (ICN) 2018 in Boston. He is the recipient of the Alexander von Humboldt Research Fellowship, the Army Research Office Young Investigator Award, the Winston Churchill Scholarship, the National Science Foundation and Office of Naval Research Graduate Fellowships, the Barry M. Goldwater Scholarship, the Frederick Emmons Terman Engineering Scholastic Award, and the President's Award for Academic Excellence (Stanford University). Professor Yeh has served as the Secretary of the Board of Governors of the IEEE Information Theory Society. He received the Best Paper Award at the 2015 IEEE International Conference on Communications (ICC) Communication Theory Symposium.


    Host: Michael Neely, mjneely@usc.edu, EEB 520, x03505

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248

    Audiences: Everyone Is Invited

    Posted By: Gerrielyn Ramos

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