TY - JOUR
T1 - The impact of network coding cluster size on approximate decoding performance
AU - Kwon, Minhae
AU - Park, Hyunggon
N1 - Funding Information:
This research was supported in part by the Ministry of Science, ICT and Future Planning (MSIP), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2015-H8501-15-1007) supervised by the Institute for Information & Communications Technology Promotion (IITP) and in part by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP; No. NRF-2014R1A2A1A11051257).
Publisher Copyright:
© 2016 KSII.
PY - 2016/3/31
Y1 - 2016/3/31
N2 - In this paper, delay-constrained data transmission is considered over error-prone networks. Network coding is deployed for efficient information exchange, and an approximate decoding approach is deployed to overcome potential all-or-nothing problems. Our focus is on determining the cluster size and its impact on approximate decoding performance. Decoding performance is quantified, and we show that performance is determined only by the number of packets. Moreover, the fundamental tradeoff between approximate decoding performance and data transfer rate improvement is analyzed; as the cluster size increases, the data transfer rate improves and decoding performance is degraded. This tradeoff can lead to an optimal cluster size of network coding-based networks that achieves the target decoding performance of applications. A set of experiment results confirms the analysis.
AB - In this paper, delay-constrained data transmission is considered over error-prone networks. Network coding is deployed for efficient information exchange, and an approximate decoding approach is deployed to overcome potential all-or-nothing problems. Our focus is on determining the cluster size and its impact on approximate decoding performance. Decoding performance is quantified, and we show that performance is determined only by the number of packets. Moreover, the fundamental tradeoff between approximate decoding performance and data transfer rate improvement is analyzed; as the cluster size increases, the data transfer rate improves and decoding performance is degraded. This tradeoff can lead to an optimal cluster size of network coding-based networks that achieves the target decoding performance of applications. A set of experiment results confirms the analysis.
KW - Approximate decoding
KW - Cluster size
KW - Internet of Things (IoT)
KW - Network coding
KW - Network optimization
KW - Wireless sensor networks (WSN)
UR - http://www.scopus.com/inward/record.url?scp=84964067860&partnerID=8YFLogxK
U2 - 10.3837/tiis.2016.03.011
DO - 10.3837/tiis.2016.03.011
M3 - Article
AN - SCOPUS:84964067860
SN - 1976-7277
VL - 10
SP - 1144
EP - 1158
JO - KSII Transactions on Internet and Information Systems
JF - KSII Transactions on Internet and Information Systems
IS - 3
ER -