一种传感网数据分类传输方法
首发时间:2019-04-04
摘要:在物联网的浪潮中,随着越来越多的传感器设备加入传感器网络,网络中的数据不再局限于标量数据的爆炸增长,越来越多的非标量数据也加入网络中。但是受网络中节点设备自身的计算能力和存储功能的局限性,混合传输标量与非标量两种数据会大大影响网络性能。本文提出节点分类模型,来应对数据混合传输情况。同时采用基于RNACK机制的丢包重传机制保证网络中各节点逐跳的传输可靠性。通过仿真计算,得到的结果显示采用分级节点模型和基于RNACK丢包重传机制可以有效提高数据包的传输效率,并降低端到端的传输时延。
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A Classified Data Transmission Method for Sensor Networks
Abstract:In the time of Internet of Things, more and more sensor devices are added to the sensor network. Type of data in sensor network is no longer limited to the explosion of scalar data. More and more non-scalar data is included. Due to the limitation of device culculation ability and storage ability, transmitting both types of data can cause low performance of the network. In this paper, we present classified-node model to handle this situation. Meanwhile, we use RNACK-based retransmission mechanism to ensure the reliability of hop-by-hop transmission. From the result of simulation, we can find that with classified-node model and RNACK-based retransmission, the sensor network can transmit more effective and reduce end-to-end delay when packet loss rate is high.
Keywords: computer network classified-node model RNACK mechanism
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