TY - GEN
T1 - Fairness in Multiterminal Data Compression
T2 - 2018 IEEE International Symposium on Information Theory, ISIT 2018
AU - Ding, Ni
AU - Smith, David
AU - Rakotoarivelo, Thierry
AU - Sadeghi, Parastoo
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8/15
Y1 - 2018/8/15
N2 - We consider the problem of how to attain fairness in the multiterminal data compression problem by a game-theoretic approach and present a decomposition method for obtaining the Shapley value, a fair source coding rate vector in the Slepian-Wolf achievable region. We model a discrete memoryless multiple random source (DMMS) by a coalitional game where the entropy function quantifies the cost incurred by the source coding rates in each coalition. In the typical case for which the game is decomposable, we show that the Shapley value can be obtained separately for each subgame. The complexity of this decomposition method is determined by the maximum size of subgames, which is strictly smaller than the total number of terminals in the DMMS and contributes to a considerable reduction in computational complexity. An experimental result demonstrates large complexity reduction when the number of terminals in the DMMS becomes large.
AB - We consider the problem of how to attain fairness in the multiterminal data compression problem by a game-theoretic approach and present a decomposition method for obtaining the Shapley value, a fair source coding rate vector in the Slepian-Wolf achievable region. We model a discrete memoryless multiple random source (DMMS) by a coalitional game where the entropy function quantifies the cost incurred by the source coding rates in each coalition. In the typical case for which the game is decomposable, we show that the Shapley value can be obtained separately for each subgame. The complexity of this decomposition method is determined by the maximum size of subgames, which is strictly smaller than the total number of terminals in the DMMS and contributes to a considerable reduction in computational complexity. An experimental result demonstrates large complexity reduction when the number of terminals in the DMMS becomes large.
UR - http://www.scopus.com/inward/record.url?scp=85052463147&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2018.8437475
DO - 10.1109/ISIT.2018.8437475
M3 - Conference contribution
SN - 9781538647806
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 886
EP - 890
BT - 2018 IEEE International Symposium on Information Theory, ISIT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 June 2018 through 22 June 2018
ER -