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长春理工大学 电子信息工程学院,吉林 长春 130022
收稿日期:2013-10-12,
修回日期:2013-09-13,
网络出版日期:2013-12-25,
纸质出版日期:2013-12-25
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陈桂芬, 王义君. 无线传感器网络跨层服务优化时间同步机制[J]. 光学精密工程, 2013,21(12): 3231-3238
CHEN Gui-Fen, WANG Yi-Jun. Optimization time synchronization in cross-layer service for WSNs[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3231-3238
陈桂芬, 王义君. 无线传感器网络跨层服务优化时间同步机制[J]. 光学精密工程, 2013,21(12): 3231-3238 DOI: 10.3788/OPE.20132112.3231.
CHEN Gui-Fen, WANG Yi-Jun. Optimization time synchronization in cross-layer service for WSNs[J]. Editorial Office of Optics and Precision Engineering, 2013,21(12): 3231-3238 DOI: 10.3788/OPE.20132112.3231.
针对无线传感器网络时间同步技术对采集时间数据依赖性强的问题,提出一种跨层服务优化时间同步机制。该技术首先对无线传感器网络链路层MAC层协议帧报头进行有效分片,利用区域划分技术重新定义网络覆盖范围。然后,对MAC层超帧结构进行调整,通过时隙退避算法解决网络中存在的隐藏节点问题。在完成MAC层优化后,在网内区域节点发送广播消息帧结构中加入时间戳,通过时间戳记录接收消息时间数据。最后,通过聚类技术对所有接收误差数据进行过滤,得到时间同步有效数据,进而补偿同步时钟漂移。仿真结果显示,在不同网络规模下与传统同步方案相比,该机制同步精度提高了8 s,收敛时间降低了10%,能量消耗不到150 mW。上述结果表明,该技术在保证时间同步精度的同时,缩短了同步收敛时间,降低了网络能量消耗。
The current time synchronization algorithms for Wireless Sensor Networks(WSNs) are dependent on the collected time data strongly. Therefore
an optimization time synchronization technology for cross-layer service was presented to work out related issues. Firstly
frame header fragmentation in a MAC layer was used for the fragment and reassembly of packets. By zoning techniques
superframe structure of the MAC layer was adjusted
and then the hidden node problem was solved through the slot backoff algorithm.Then
a timestamp was added into the frame structure of the broadcast message to record the time data of received messages
and all received error data were filtered through clustering techniques. Also the synchronous clock drift was compensated. The simulation results indicate that the time synchronization accuracy is improved by 8 s
the convergence time is reduced by 10% and the energy consumption is less than 150 mW compared with those of other traditional algorithms.These results prove that the technology ensures the accuracy
and simultaneously reduces the convergence time and the energy consumption of the network.
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