计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 596-598.doi: 10.11896/JsJkx.190900194

• 交叉&应用 • 上一篇    下一篇

基于6LoWPAN的低功耗长距离海洋环境监测系统

王栋1, 王虎2, 姜迁里3   

  1. 1 中国海洋大学图书馆 山东 青岛 266100;
    2 中国海洋发展研究中心 山东 青岛266100;
    3 中国海洋大学海洋高等研究院 山东 青岛 266100
  • 发布日期:2020-07-07
  • 通讯作者: 姜迁里(Jiangqianli621@126.com)
  • 作者简介:wangdong@ouc.edu.cn
  • 基金资助:
    中央高校基本科研业务费专项中国海洋大学图书情报研究基金(201953001);赛尔网络下一代互联网技术创新项目 (NGII20170309)

Low Power Long Distance Marine Environment Monitoring System Based on 6LoWPAN

WANG Dong1, WANG Hu2 and JIANG Qian-li3   

  1. 1 Library,OceanUniversity of China,Qingdao,Shangdong 266100,China
    2 Academy of Ocean of China,Qingdao,Shangdong 266100,China
    3 Institute for Advanced Ocean Study,Ocean University of China,Qingdao,Shangdong 266100,China
  • Published:2020-07-07
  • About author:WANG Dong, Ph.D.His research areas are machine vision, embedded system, software programming, and IoT design.JIANG Qian-li, Ph.D.His research areas are underwater robots, and ROV design.
  • Supported by:
    This work was supported by the Fundamental Research Funds for the Central Universities (201953001) and CERNET Innouation ProJect (NGII20170309).

摘要: 海洋环境监测具有监测节点分散、节点数量多、测量数据种类复杂、信息交换和通信业务多样性的特点。无线传感器网络可以减少线路连接,降低部署和运维成本。6LoWPAN(IPv6 over Low-Power Wireless Personal AreaNetworks)技术基于IEEE802.15.4实现了IPV6数据包在无线传感器网络中的传输,是实现无线传感器网络和因特网互联的理想技术。在研究Contiki 6LoWPAN网络拓扑结构和协议的基础上,文中采用TI CC1310平台搭建了无线传感器节点和边缘路由器,节点数据经过边缘路由器和互联网,最终发送到服务器监控系统,实现海洋数据的动态监测。通过实验证明,该系统具有组网简单、传输距离远、成本和功耗低等优势。

关键词: CC1310, IPv6, 海洋环境监测, 无线传感器网络

Abstract: Marine environmental monitoring is characterized with decentralized monitoring nodes,a large quantity of nodes,complicated of measurement data types,variety of information exchange and communication.Wireless sensor networks can reduce the number of cable connections,and decrease the costs of deployment and maintenance.Based on IEEE802.15.4,6LoWPAN technology realizes the transmission of IPV6 data packets in wireless sensor networks,hence it is an ideal technology for the interconnection between wireless sensor network and Internet.Based on the research of the topology and protocol of Contiki 6LoWPAN network,the TI CC1310 platform is used to build the wireless sensor nodes and edge routers.The node data is sent to the monitoring system on severs through the edge routers and Internet,to achieve the dynamic monitoring of ocean data.Experiments show that the system has the advantages of easy network construction,long transmission distance,and low cost and power consumption.

Key words: CC1310, IPv6, Marine environmental monitoring, Wireless sensor network

中图分类号: 

  • TP393
[1] 崔振东,郑亮,桂福坤,等.海-岛感知物联网关键技术研究.浙江海洋学院学报(自然科学版),2015,34(2):204-208.
[2] 綦声波,吴学英.基于6LoWPAN的海洋台站监测系统.海洋技术学报,2017,36(6):38-43.
[3] 杨祯明.基于海洋环境数据的物联网动态监测系统设计.舰船科学技术,2017,39(6):153-155.
[4] ZHAO H G,SHI C,ZHAI L Y.Design and Implementation of Lightweight 6LoWPAN Gateway Based on Contiki//2018 IEEE International Conference on Signal Processing,Communications and Computing (ICSPCC).Qingdao,2018:1-5.
[5] 胡国强,杨彦荣.基于6LoWPAN和IPv6的猪舍环境远程监测系统.计算机测量与控制,2019,27(5):9-12.
[6] 黄小兵,聂兰顺.无线自组网节点极低基础功耗方案的设计.智能计算机与应用,2018,8(6):225-229.
[7] SOMMER P,MARET Y,DZUNG D.Low-Power Wide-Area Networks for Industrial Sensing Applications//2018 IEEE International Conference on Industrial Internet (ICII).Seattle,WA,2018:23-32.
[8] HUANG L T,HA D S,CHO H.Low Power Design of a Wireless Sensor Node to Monitor Electric Car Batteries//IECON 2018-44th Annual Conference of the IEEE Industrial Electronics Society.Washington,DC,2018:3045-3050.
[1] 范星泽, 禹梅.
改进灰狼算法的无线传感器网络覆盖优化
Coverage Optimization of WSN Based on Improved Grey Wolf Optimizer
计算机科学, 2022, 49(6A): 628-631. https://doi.org/10.11896/jsjkx.210500037
[2] 王国武, 陈元琰.
基于跳数修正和遗传模拟退火优化DV-Hop定位算法
Improvement of DV-Hop Location Algorithm Based on Hop Correction and Genetic Simulated Annealing Algorithm
计算机科学, 2021, 48(6A): 313-316. https://doi.org/10.11896/jsjkx.201000101
[3] 赵志强, 易秀双, 李婕, 王兴伟.
基于GR-AD-KNN算法的IPv6网络DoS入侵检测技术研究
Research on DoS Intrusion Detection Technology of IPv6 Network Based on GR-AD-KNN Algorithm
计算机科学, 2021, 48(6A): 524-528. https://doi.org/10.11896/jsjkx.200500001
[4] 刘宁宁,樊建席,林政宽.
基于地址空间的树型网络地址分配
Address Assignment Algorithm for Tree Network Based on Address Space
计算机科学, 2020, 47(2): 239-244. https://doi.org/10.11896/jsjkx.190400130
[5] 苏凡军,杜可怡.
WSNs中基于信任度的节能机会路由算法
Trust Based Energy Efficient Opportunistic Routing Algorithm in Wireless Sensor Networks
计算机科学, 2020, 47(2): 300-305. https://doi.org/10.11896/jsjkx.190100172
[6] 周文祥, 乔学工.
基于能量优化的无线传感器网络任播路由算法
Anycast Routing Algorithm for Wireless Sensor Networks Based on Energy Optimization
计算机科学, 2020, 47(12): 291-295. https://doi.org/10.11896/jsjkx.190900069
[7] 李正阳, 陶洋, 周远林, 杨柳.
基于能量获取的能耗均衡多跳分簇路由协议
Energy-balanced Multi-hop Cluster Routing Protocol Based on Energy Harvesting
计算机科学, 2020, 47(11A): 296-302. https://doi.org/10.11896/jsjkx.200300002
[8] 侯明星,亓慧,黄斌科.
基于分布式压缩感知的无线传感器网络异常数据处理
Data Abnormality Processing in Wireless Sensor Networks Based on Distributed Compressed Sensing
计算机科学, 2020, 47(1): 276-280. https://doi.org/10.11896/jsjkx.180901667
[9] 王改云, 王磊杨, 路皓翔.
基于混合群智能算法优化的RSSI质心定位算法
RSSI-based Centroid Localization Algorithm Optimized by Hybrid Swarm Intelligence Algorithm
计算机科学, 2019, 46(9): 125-129. https://doi.org/10.11896/j.issn.1002-137X.2019.09.017
[10] 刘静, 赖英旭, 杨胜志, Lina Xu.
一种面向WSN的双向身份认证协议及串空间模型
Bilateral Authentication Protocol for WSN and Certification by Strand Space Model
计算机科学, 2019, 46(9): 169-175. https://doi.org/10.11896/j.issn.1002-137X.2019.09.024
[11] 王静, 仇晓鹤.
基于分簇和融合补偿策略的多维标度定位算法
Advanced MDS-MAP Localization Algorithm with Clustering and Fusion Compensation Strategy
计算机科学, 2019, 46(8): 145-151. https://doi.org/10.11896/j.issn.1002-137X.2019.08.024
[12] 叶娟, 陈元琰, 王明, 尼迎波.
多通信半径与角度修正的凸规划改进定位算法
Optimized Convex Localization Algorithm Using Multiple Communication Radius and Angle Correction
计算机科学, 2019, 46(6A): 317-320.
[13] 梁平元, 李杰, 彭娇, 王会.
基于协作MIMO的UWSN三维动态分簇路由算法研究
Research on 3D Dynamic Clustering Routing Algorithm Based on Cooperative MIMO for UWSN
计算机科学, 2019, 46(6A): 336-342.
[14] 李秀琴, 王天荆, 白光伟, 沈航.
基于压缩感知的两阶段多目标定位算法
Two-phase Multi-target Localization Algorithm Based on Compressed Sensing
计算机科学, 2019, 46(5): 50-56. https://doi.org/10.11896/j.issn.1002-137X.2019.05.007
[15] 孙博文, 韦素媛.
基于自适应调整策略灰狼算法的DV-Hop定位算法
DV-Hop Localization Algorithm Based on Grey Wolf Optimization Algorithm with
Adaptive Adjutment Strategy
计算机科学, 2019, 46(5): 77-82. https://doi.org/10.11896/j.issn.1002-137X.2019.05.012
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!