TY - JOUR
T1 - Coding for Distributed Fog Computing
AU - Li, Songze
AU - Maddah-Ali, Mohammad Ali
AU - Salman Avestimehr, A.
N1 - Publisher Copyright:
© 1979-2012 IEEE.
PY - 2017
Y1 - 2017
N2 - Redundancy is abundant in fog networks (i.e., many computing and storage points) and grows linearly with network size. We demonstrate the transformational role of coding in fog computing for leveraging such redundancy to substantially reduce the bandwidth consumption and latency of computing. In particular, we discuss two recently proposed coding concepts, minimum bandwidth codes and minimum latency codes, and illustrate their impacts on fog computing. We also review a unified coding framework that includes the above two coding techniques as special cases, and enables a trade-off between computation latency and communication load to optimize system performance. At the end, we will discuss several open problems and future research directions.
AB - Redundancy is abundant in fog networks (i.e., many computing and storage points) and grows linearly with network size. We demonstrate the transformational role of coding in fog computing for leveraging such redundancy to substantially reduce the bandwidth consumption and latency of computing. In particular, we discuss two recently proposed coding concepts, minimum bandwidth codes and minimum latency codes, and illustrate their impacts on fog computing. We also review a unified coding framework that includes the above two coding techniques as special cases, and enables a trade-off between computation latency and communication load to optimize system performance. At the end, we will discuss several open problems and future research directions.
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U2 - 10.1109/MCOM.2017.1600894
DO - 10.1109/MCOM.2017.1600894
M3 - Article
AN - SCOPUS:85018768039
SN - 0163-6804
VL - 55
SP - 34
EP - 40
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
IS - 4
M1 - 7901473
ER -