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Abstract
The control of congestion is very important in the parallel transmission of blockchain-based data over high-speed networks. There are drawbacks to the conventional methods, such as interference between different transmission paths, the collision of data, and channel allocation policies to address these problems, there is a need to investigate newer methods for controlling the congestion on multipath channels for parallel transmission of data. The conventional methods cannot reduce the data packet queuing time, the packet loss rate, and latency time of packets. In parallel data transfer, especially in blockchain-based transactions, congestion control is critical. This research proposes and implements a data congestion control approach for multipath parallel transmission on IoT networks. The multipath parallel transmission path is established in this research work to enable the source node to sense the path congestion information in a real-time environment. Finally, the low congestion path is selected to avoid congestion for parallel data transmission and to achieve high throughput over the network channels. The simulation results show that the strategy provided in this paper minimizes data packet queuing time efficiently, boosts network channel throughput, and decreases data packet loss rate.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the author(s).
Data availability statement
The data that support the findings of this study will be made available upon reasonable request.
Additional information
Funding
Notes on contributors
Liqiong Huang
Liqiong Huang was born in June 1987. She received a Bachelor’s degree in Mathematics and Applied Mathematics from the Department of Mathematics and Applied Mathematics of the Xi’an University in 2000. She received master’s in Applied Mathematics from the School of Mathematics and Information Science of Shaanxi Normal University in 2013. She has been working as a lecturer at Shangluo University since 2013. Her research interests focus on nonlinear systems and switched systems. She has published six academic papers and conducted three scientific research projects. Corresponding author. Email: [email protected]
Yuanyuan Wang
Yuanyuan Wang was born in August 1987. She received a Bachelor's degree in Measurement and Control Technology and Instruments from the Xi’an Shiyou University in 2000. She received a master’s in Signal and Information Processing from the Xi’an Shiyou University in 2013. She has been working at Shangluo University since 2013. Her research interests focus on signal processing and image processing. She has published eight academic papers and conducted two scientific research projects. E-mail: [email protected]