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Optimal topological balancing strategy for performance optimisation of consensus-based clock synchronisation protocols in wireless sensor networks: a genetic algorithm-based approach

机译:无线传感器网络中基于共识的时钟同步协议性能优化的最佳拓扑平衡策略:一种基于遗传算法的方法

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Consensus-based clock synchronisation (CCS) protocols have gained recent attention in wireless sensor networks. However, the well-known and state-of-the-art protocols are ‘all node based’, that is, every node iterates the consensus algorithm to reach to the synchronised state by exchanging synchronisation messages with the neighbours. This increases the congestion in the network because of extensive message exchanges and induces packet losses and delay in the network. Hence, it is desirable that a subset of connected sensors along with a balanced number of neighbouring sensors should be selected to form a logical topology which will serve as a virtual backbone for the CCS algorithm. This will minimise the overall message complexity and energy consumption in the network as well as balances and minimises delay for faster consensus convergence with optimal synchronisation error. This problem is claimed to be a generalisation of Load Balanced Connected Dominating Set problem which is recently proved to be NP-complete. To make the problem tractable, a genetic algorithm-based strategy is proposed to select the synchronising nodes to form an optimal logical topology.
机译:基于共识的时钟同步(CCS)协议最近在无线传感器网络中受到关注。但是,众所周知的最新协议是“基于所有节点”的,也就是说,每个节点都通过与邻居交换同步消息来迭代共识算法以达到同步状态。由于大量的消息交换,这会增加网络的拥塞,并导致数据包丢失和网络延迟。因此,期望应当选择连接的传感器的子集以及平衡数量的相邻传感器,以形成逻辑拓扑,该逻辑拓扑将用作CCS算法的虚拟主干。这将最大程度地降低整体消息的复杂性和网络中的能量消耗,并实现平衡,并最大程度地减少延迟,以实现更快的共识收敛和最佳同步错误。该问题据称是负载平衡连接支配集问题的一般化,最近被证明是NP完全的。为了使问题易于解决,提出了一种基于遗传算法的策略来选择同步节点以形成最佳逻辑拓扑。

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