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Energy-aware scheduling for information fusion in wireless sensor network surveillance

机译:无线传感器网络监控中信息融合的能量感知调度

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Effective energy control while maintaining reliable monitoring performance becomes a key issue in wireless sensor networks (WSNs) based surveillance applications. While importance difference of surveillance zone, limited energy and dynamic network topology pose great challenges to surveillance performance. It is necessary to adjust sensor nodes' awakening frequency dynamically for information fusion. Thus an energy-aware scheduling with quality guarantee method named ESQG is proposed in this paper which considers sensor nodes' residual energy, different importance degrees of the surveillance zone and network topology comprehensively. It first uses a Voronoi diagram to determine the effective scope of each sensor node and then calculates node importance according to its residual energy and the importance degree of the effective scope. Then ESQG utilizes the importance of individual sensing scope and current forwarding costs to further compute node importance and awakening frequency for information fusion. In this way, ESQG can dynamically adapts each nodes awakening frequency to its dynamic network topology and importance degree of each individual sensing scope. The nodes are then turned on stochasticlly via the node awakening probability and node importance based information fusion is conducted for target detection. Besides, an adaptive process of perception factor C is proposed to match actual situation, and automatically change according to the detected data. Experiments results demonstrate that the proposed method ESQG can reduce the number of awakening nodes to a large extent while maintaining high reliability via information fusion.
机译:有效的能量控制,同时保持可靠的监控性能成为无线传感器网络(WSNS)监视应用中的关键问题。虽然监控区的重要差异,有限的能量和动态网络拓扑构成了监视性能的巨大挑战。有必要为信息融合动态调整传感器节点唤醒频率。因此,在本文中提出了具有名为ESQG的质量保证方法的能量感知调度,其认为传感器节点的剩余能量,监视区域和网络拓扑的不同程度。首先使用Voronoi图来确定每个传感器节点的有效范围,然后根据其剩余能量和有效范围的重要程度来计算节点重要性。然后ESQG利用个人传感范围和当前转发成本的重要性,以进一步计算信息融合的节点重要性和唤醒频率。以这种方式,ESQG可以动态地将每个节点唤醒频率调整到其动态网络拓扑和每个单独传感范围的重要程度。然后通过节点唤醒概率随机打开节点,并对基于节点重要的信息融合进行针对目标检测。此外,提出了一种感知因子C的自适应过程来匹配实际情况,并根据检测到的数据自动改变。实验结果表明,所提出的方法ESQG可以在很大程度上减少唤醒节点的数量,同时通过信息融合保持高可靠性。

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