TY - GEN
T1 - Compressed network coding
T2 - 2014 IEEE Wireless Communications and Networking Conference, WCNC 2014
AU - Kwon, Minhae
AU - Park, Hyunggon
AU - Frossard, Pascal
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2016/4/3
Y1 - 2016/4/3
N2 - In this paper, we consider a delay-sensitive data transmission strategy based on network coding technique in finite fields over error-prone networks. In order to solve all-or-nothing problem inherited from network coding, compressed network coding is proposed by jointly considering network coding techniques and compressed sensing technique. While network coding techniques have been jointly used with the compressed sensing techniques, network coding operations are performed in the field of real numbers, and thus, the payload of transmitted data can be enlarged as the data traverse more hops in networks. In this paper, however, we propose to use network coding techniques in finite fields, such that the size of payload does not increase as more hops are traversed. With the help of compressed sensing technique, a destination node is able to approximately recover the source data based on l1-norm minimization approach, in case of innovative packet loss. It is analytically shown that the payload size of the proposed approach is always smaller than that of the conventional approach, while the proposed approach can achieve comparable decoding performances. We evaluate the effectiveness of the proposed approach based on an illustrative application of image delivery system.
AB - In this paper, we consider a delay-sensitive data transmission strategy based on network coding technique in finite fields over error-prone networks. In order to solve all-or-nothing problem inherited from network coding, compressed network coding is proposed by jointly considering network coding techniques and compressed sensing technique. While network coding techniques have been jointly used with the compressed sensing techniques, network coding operations are performed in the field of real numbers, and thus, the payload of transmitted data can be enlarged as the data traverse more hops in networks. In this paper, however, we propose to use network coding techniques in finite fields, such that the size of payload does not increase as more hops are traversed. With the help of compressed sensing technique, a destination node is able to approximately recover the source data based on l1-norm minimization approach, in case of innovative packet loss. It is analytically shown that the payload size of the proposed approach is always smaller than that of the conventional approach, while the proposed approach can achieve comparable decoding performances. We evaluate the effectiveness of the proposed approach based on an illustrative application of image delivery system.
KW - Compressed sensing
KW - Delay sensitive data
KW - In-network compression
KW - Network coding
KW - the Galois field
UR - http://www.scopus.com/inward/record.url?scp=84912118320&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2014.6952901
DO - 10.1109/WCNC.2014.6952901
M3 - Conference contribution
AN - SCOPUS:84912118320
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 2851
EP - 2856
BT - IEEE Wireless Communications and Networking Conference, WCNC
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 April 2014 through 9 April 2014
ER -