L-SYNC: Larger Degree Clustering Based Time-Synchronisation for Wireless Sensor Network

Masoume Jabbarifar, Alireza Shameli-Sendi, H. Pedram, M. Dehghan, M. Dagenais
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引用次数: 13

Abstract

In many existing synchronization protocols within wireless sensor networks, the effect of routing algorithm in synchronization precision of two remote nodes is not being considered. In several protocols such as SLTP, this issue is considered for local time estimation of a remote node. Cluster creation is according to ID technique. This technique incurs an increase in cluster overlapping and eventually the routing algorithm will be affected and requires more hops to move from one cluster to another remote cluster. In this article, we present L-SYNC method, which creates large degree clusters for wireless sensor networks synchronization. Using large degree clustering, L-SYNC can reduce path hops. Also, L-SYNC uses linear regression method to calculate clock offset and skew in each cluster. Therefore, it is capable to compute skew and offset intervals between each node and its head cluster and, in other words, it can estimate the local time of remote nodes in future and past. To estimate the local time for remote nodes, routing algorithm is used and conversion technique is performed in each time changing hop. The fewer L-SYNC hops could increase the precision. Simulation results illustrate that monotonous clustering formation can increase the precision in synchronization. However, more overhead and time period are needed for clustering formation
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L-SYNC:基于大程度聚类的无线传感器网络时间同步
在现有的无线传感器网络同步协议中,没有考虑路由算法对远端节点同步精度的影响。在SLTP等几个协议中,这个问题被考虑用于远程节点的本地时间估计。集群的创建是基于ID技术的。这种技术导致集群重叠的增加,最终路由算法将受到影响,并且需要从一个集群移动到另一个远程集群更多的跳数。在本文中,我们提出了L-SYNC方法,该方法为无线传感器网络同步创建了大度簇。使用大程度聚类,L-SYNC可以减少路径跳转。此外,L-SYNC使用线性回归方法计算每个集群中的时钟偏移和倾斜。因此,它能够计算每个节点与其头簇之间的倾斜和偏移间隔,换句话说,它可以估计未来和过去远程节点的本地时间。为了估计远端节点的本地时间,采用了路由算法,并在每一时变跳中进行转换技术。更少的L-SYNC跳数可以提高精度。仿真结果表明,单调聚类可以提高同步精度。然而,集群形成需要更多的开销和时间周期
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