一种基于SDN的物联网数据聚合方案

王博伟; 谭劲; 蒋文斌

doi:10.11959/j.issn.1000-0801.2019028

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一种基于SDN的物联网数据聚合方案

研究与开发 | 更新时间：2024-06-05

- 一种基于SDN的物联网数据聚合方案
- Data aggregation scheme based on SDN for internet of things
- 电信科学 2019年35卷第2期页码：27-34
- 作者机构：
- 作者简介：
  
  [ "王博伟（1994- ），男，中国计量大学信息工程学院硕士生，主要研究方向为物联网、无线传感网。" ]
  [ "谭劲（1962- ），男，博士后，中国计量大学信息工程学院副教授，主要研究方向为无线网络与通信、多媒体技术。" ]
  [ "蒋文斌（1997- ），男，中国计量大学信息工程学院硕士生，主要研究方向为无线体域网、无线传感网。" ]
- 基金信息：
  
  浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China(LY16F020013)
- DOI：10.11959/j.issn.1000-0801.2019028
  中图分类号： TP393
- 网络出版日期：2019-02，
  
  纸质出版日期：2019-02-20
- 稿件说明：
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王博伟, 谭劲, 蒋文斌. 一种基于SDN的物联网数据聚合方案[J]. 电信科学, 2019,35(2):27-34.

Bowei WANG, Jin TAN, Wenbin JIANG. Data aggregation scheme based on SDN for internet of things[J]. Telecommunications science, 2019, 35(2): 27-34.
王博伟, 谭劲, 蒋文斌. 一种基于SDN的物联网数据聚合方案[J]. 电信科学, 2019,35(2):27-34. DOI： 10.11959/j.issn.1000-0801.2019028.

Bowei WANG, Jin TAN, Wenbin JIANG. Data aggregation scheme based on SDN for internet of things[J]. Telecommunications science, 2019, 35(2): 27-34. DOI： 10.11959/j.issn.1000-0801.2019028.

摘要

物联网设备产生和发送的数据中存在许多重复冗余的部分，传输这些数据降低了网络寿命和带宽。针对这个问题提出了聚合网关层，设计了一种基于SDN的物联网数据聚合体系结构和算法。仿真分析表明，设计的体系结构与普通网关和OF-GW的体系结构相比，网络寿命提高了约32.6%，感知层发送到网络层中的数据分组量减少了6.1%～55.1%，设计的规则算法与LEACH算法相比，数据聚合的平均时延降低了约24.1%，同时避免了数据缺失，提高了数据聚合的准确性。

Abstract

There are many redundant parts in the data generated and transmitted by IoT devices.Transmitting this data reduces network lifetime and bandwidth.Aiming at the problem

the aggregation gateway layer was proposed

and a SDN-based IoT data aggregation architecture and algorithm were designed.The simulation analysis shows that compared with the architecture of the ordinary gateway and OF-GW

the network lifetime is improved by about 32.6%

and the amount of data packets sent by the sensing layer to the network layer is reduced by 6.1% to 55.1%.Compared with the LEACH algorithm

the designed rule algorithm reduces the average delay of data aggregation by about 24.1%

while avoiding data loss and improving the accuracy of data aggregation.

关键词

Keywords

references

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