基于被动分簇的时间同步容错技术研究
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摘要
在传统的时间同步容错算法中,簇内节点间的容错无法准确到整个传感器网络,簇间时间同步误差大,且分簇方式没有考虑能耗问题。针对以上问题,提出了一种基于被动分簇的时间同步容错技术。该技术采用被动分簇方式,节省了大量能耗。在被动分簇形成的水声传感器网络中,将布置区域划分为多个圆形的簇区域。在簇内节点间,正常节点与正常节点之间的时钟差异有一个上限,一个节点自身时钟的调整也存在一个上限。在簇头节点之间,根据簇内节点得到簇头节点间时钟差异存在上限。实验结果表明,相比于传统的时间同步容错技术,该方案减少了恶意节点的数量,提高了节点的利用率。由于节点之间同步时采用轮流广播的形式,该方案正常节点之间不会产生同步信息的碰撞问题。
In the traditional time synchronization fault-tolerant algorithm,the fault tolerance between cluster nodes cannot be accurate to the whole sensor network,the time synchronization error between the clusters is large,and the energy consumption is not considered in the clustering mode. Aiming at the above problems,we propose a time synchronization fault-tolerant technique based on passive clustering,which saves a lot of energy consumption by passive clustering. In the underwater acoustic sensor network formed by passive clustering,the layout area is divided into a plurality of circular cluster areas. Among nodes in the cluster,there is an upper limit of clock difference between normal nodes and also one of clock adjustment of a node itself. According to the intra-cluster nodes,there is an upper limit of clock difference between cluster heads. Experiment shows that compared with the traditional time synchronization fault-tolerant technology,this scheme reduces the number of malicious nodes and improves the utilization rate of nodes. Since the synchronization between nodes is in the form of alternate broadcast,there is no collision of synchronization information between normal nodes in this scheme.
In the traditional time synchronization fault-tolerant algorithm,the fault tolerance between cluster nodes cannot be accurate to the whole sensor network,the time synchronization error between the clusters is large,and the energy consumption is not considered in the clustering mode. Aiming at the above problems,we propose a time synchronization fault-tolerant technique based on passive clustering,which saves a lot of energy consumption by passive clustering. In the underwater acoustic sensor network formed by passive clustering,the layout area is divided into a plurality of circular cluster areas. Among nodes in the cluster,there is an upper limit of clock difference between normal nodes and also one of clock adjustment of a node itself. According to the intra-cluster nodes,there is an upper limit of clock difference between cluster heads. Experiment shows that compared with the traditional time synchronization fault-tolerant technology,this scheme reduces the number of malicious nodes and improves the utilization rate of nodes. Since the synchronization between nodes is in the form of alternate broadcast,there is no collision of synchronization information between normal nodes in this scheme.
引文
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[2]吴琼.无线传感器网络时间同步算法研究[D].天津:天津大学,2016.
[3]司海飞,杨忠,王珺.无线传感器网络研究现状与应用[J].机电工程,2011,28(1):16-20.
[4]于海涛.水声传感器网络路由协议的研究[D].哈尔滨:哈尔滨工程大学,2016.
[5] LIU Tongqing,HAN Guangjie,ZHU Chuan,et al. Application research on aqua-sim for underw ater acoustic sensor netw orks[J]. Advanced M aterials Research,2012,605-607:1046-1049.
[6]王贤德,贾连兴.基于DTS和IEEE1588v2协议的网络跳变同步技术研究[J].装甲兵工程学院学报,2017,31(4):87-92.
[7]张可,尹涛,刘群,等.一种应用于行波测距装置的高精度时间同步技术[J].工业仪表与自动化装置,2017(4):101-104.
[8]王竹刚.星载高精度测距与时间同步技术研究[D].北京:中国科学院大学(中国科学院国家空间科学心),2017.
[9]张天禹.无线传感器网络时间同步算法研究[D].长春:长春理工大学,2017.
[10]杨东.基于分簇型无线传感器网络时间同步机制的研究[D].太原:太原理工大学,2013.
[11]陈乔.无线传感器网络时间同步算法的研究与应用[D].西安:西安理工大学,2010.
[12]刘敏,惠力,杨立,等.水声传感器网络及其在海洋监测中的应用研究[J].山东科学,2010,23(2):22-27.
[13]赵旦峰,梁明珅,段晋珏.水声网络中喷泉码的应用研究现状与发展前景[J].系统工程与电子技术,2014,36(9):1838-1843.
[14] KANTHIMATHI N,DHARMA D. Balanced and multi-objective optimized opportunistic routing for underw ater sensor netw orks[J]. Wireless Personal Communications,2016,94(4):2417-2440.
[15]李秋灵.无线传感器网络时间同步技术容错性的研究[D].北京:华北电力大学,2014.
[16] ZHAN Chuan,LU Xianliang,ZHOU Xu,et al. An improved Bayesian w ith application to anti-spam email[J]. Journal of Electronic Science and Technology of China,2005,3(1):30-33.
[17] KRISHNAMURTHY L,ADLER R,BUONADONNA P,et al. Design and deployment of industrial sensor netw orks:experiences from a semiconductor plant and the north sea[C]//Proceedings of the 3rd international conference on embedded netw orked sensor systems. San Diego,CA,USA:[s. n.],2005:64-75.
[18] BURRELL J,BROOKE T,BECKWITH R. Vineyard computing:sensor netw orks in agricultural production[J]. IEEE Pervasive Computing,2004,3(1):38-45.
[19] CAMILLI A,CUGNASCA E,SARAIVA M,et al. From w ireless sensors to field mapping:anatomy of an application for precision agriculture[J]. Computers and Electronics in Agriculture,2007,58(1):25-36.