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Desmond S. Lun
Researcher at Rutgers University
Publications - 99
Citations - 6154
Desmond S. Lun is an academic researcher from Rutgers University. The author has contributed to research in topics: Linear network coding & Network packet. The author has an hindex of 34, co-authored 95 publications receiving 5823 citations. Previous affiliations of Desmond S. Lun include Australian Centre for Plant Functional Genomics & University of Illinois at Urbana–Champaign.
Papers
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Journal ArticleDOI
On Coding for Reliable Communication over Packet Networks
TL;DR: In this article, the authors present a capacity-achieving coding scheme for unicast or multicast over lossy packet networks, where intermediate nodes perform additional coding yet do not decode nor even wait for a block of packets before sending out coded packets.
Journal ArticleDOI
Full length article: On coding for reliable communication over packet networks
TL;DR: In this paper, the authors consider the use of random linear network coding in lossy packet networks and show that it achieves packet-level capacity for both single unicast and single multicast connections and for both wireline and wireless networks.
Journal ArticleDOI
Minimum-cost multicast over coded packet networks
Desmond S. Lun,N. Ratnakar,Muriel Medard,Ralf Koetter,David R. Karger,Tracey Ho,Ebad Ahmed,Fang Zhao +7 more
TL;DR: This work reduces the problem of establishing minimum-cost multicast connections over coded packet networks to a polynomial-time solvable optimization problem, and presents decentralized algorithms for solving it.
Book
Network Coding: An Introduction
Tracey Ho,Desmond S. Lun +1 more
TL;DR: The first book to present a unified and intuitive overview of the theory, applications, challenges, and future directions of this emerging field, this is a must-have resource for those working in wireline or wireless networking.
Journal ArticleDOI
Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.
Caroline Colijn,Caroline Colijn,Caroline Colijn,Aaron Brandes,Jeremy Zucker,Desmond S. Lun,Desmond S. Lun,Brian Weiner,Maha R. Farhat,Tan-Yun Cheng,D. Branch Moody,Megan Murray,James E. Galagan,James E. Galagan +13 more
TL;DR: E-Flux as mentioned in this paper extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression, which can predict changes in metabolic flux capacity.