Anti-Congestion Algorithm for Multiple Data Unicast Transmission in the Internet of Brain Things
Anti-Congestion Algorithm for Multiple Data Unicast Transmission in the Internet of Brain Things
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DOI：
10.1109/access.2018.2883684
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发表时间：
2018
期刊：
影响因子：
3.9
通讯作者：
Xiaodan Yan;Wei Yan;Liangxiu Zhang
中科院分区：
文献类型：
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作者：
Xiaodan Yan;Wei Yan;Liangxiu Zhang
针对传统脑物联网传输中存在的串扰、信道竞争、数据传输拥塞等问题，提出了一种新的多数据单播传输抗拥塞算法。该算法通过对大脑物联网中的多个数据传输通道建立多维冲突模型，计算多个数据单播的拥塞概率。本发明根据网络数据传输通道路径在空间上的串扰特性，检测多个数据单播传输的拥塞情况，并将单播传输在大脑物联网中的拥塞状态反向检测拥塞通道，从而减少易发生串扰的数据传输。为实现抗拥塞传输，对该方法进行了仿真实验。实验结果表明，该方法能够准确检测多数据单播传输中的信道路径冲突信息。它具有高数据传输性能，有助于未来物联网大脑中各种数据的拥塞传输。
Aiming at the problems of traditional cross-talk, channel competition, and data transmission congestion in the brain Internet of Things transmission, a new anti-congestion algorithm for multi-data unicast transmission is proposed. The algorithm calculates the congestion probability of multiple data unicasts by establishing a multi-dimensional conflict model for multiple data transmission channels in the brain Internet of Things. According to the crosstalk characteristic of the network data transmission channel path in the space, the congestion condition of multiple data unicast transmission is detected, and the congestion state of the unicast transmission in the brain Internet of Things is reversed to detect the congestion channel, thereby reducing the congestion-prone data transmission. To achieve anti-congestion transmission, the simulation experiment is carried out on the method. The experimental results show that the method can accurately detect channel path conflict information in multiple data unicast transmissions. It has high-data transmission performance and contributes to the congestion transmission of various data in the brain of the Internet of Things in the future.