TY - GEN
T1 - The cluster formation strategies for approximate decoding in IoT networks
AU - Kwon, Minhae
AU - Park, Hyunggon
N1 - Funding Information:
This research was supported in part by by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2015-H8501-15-1007) supervised by the IITP (Institute for Information & Communications Technology Promotion) and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2014R1A2A1A11051257)).
Publisher Copyright:
© 2016 IEEE.
PY - 2016/3/7
Y1 - 2016/3/7
N2 - In this paper, we consider delay-constrained data transmission based on network coding techniques over error-prone IoT networks. While network coding approaches can provide various advantages, there is a critical drawback referred to as all-or-nothing problem; the encoded source data cannot be recovered if a set of required number of data is not entirely received by a decoding deadline. As a solution, an approximate decoding approach has been proposed. In this paper, we quantify the performance of approximate decoding and show that the performance is determined only by the insufficient number of packets. Moreover, we analytically show the fundamental tradeoff between the performance of the approximate decoding and data transfer rate improvement; as the cluster size increases, data transfer rate is improved while the 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. The analysis is confirmed by a set of experiments.
AB - In this paper, we consider delay-constrained data transmission based on network coding techniques over error-prone IoT networks. While network coding approaches can provide various advantages, there is a critical drawback referred to as all-or-nothing problem; the encoded source data cannot be recovered if a set of required number of data is not entirely received by a decoding deadline. As a solution, an approximate decoding approach has been proposed. In this paper, we quantify the performance of approximate decoding and show that the performance is determined only by the insufficient number of packets. Moreover, we analytically show the fundamental tradeoff between the performance of the approximate decoding and data transfer rate improvement; as the cluster size increases, data transfer rate is improved while the 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. The analysis is confirmed by a set of experiments.
KW - Approximate decoding
KW - Clustering
KW - Delay-constrained data transmission
KW - Internet of Things (IoT)
KW - Network coding
KW - Wireless Sensor Networks (WSN)
UR - http://www.scopus.com/inward/record.url?scp=84963956110&partnerID=8YFLogxK
U2 - 10.1109/ICOIN.2016.7427134
DO - 10.1109/ICOIN.2016.7427134
M3 - Conference contribution
AN - SCOPUS:84963956110
T3 - International Conference on Information Networking
SP - 366
EP - 368
BT - 30th International Conference on Information Networking, ICOIN 2016
PB - IEEE Computer Society
T2 - 30th International Conference on Information Networking, ICOIN 2016
Y2 - 13 January 2016 through 15 January 2016
ER -