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Error Analysis and Kernel Density Approach of Scheduling Sleeping Nodes in Cluster-Based Wireless Sensor Networks

机译:基于集群的无线传感器网络中睡眠节点调度的误差分析和核密度方法

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摘要

Energy consumption is an important research topic in wireless sensor networks. Putting sensor nodes to sleep is one of the most popular ways to save energy in battery-powered sensor nodes. Many existing research studies on sleeping techniques are based on preknowledge of deployment of sensor nodes, e.g., a known probability distribution of sensor nodes in a target-sensing field. Thus, whether a scheduling-sleeping scheme has good performance mostly depends on preknowledge of the deployment of sensor nodes. In this paper, we first show the discrepancy of system performance metrics, including energy consumption and network lifetime, based on inaccurate preknowledge of the deployment of sensor nodes in a cluster-based sensor network. Through analytical studies, we conclude that the discrepancy is very large and cannot be neglected. We hence propose a distribution-free approach to study energy consumption. In our approach, no assumption of the probability distribution of deployment of sensor nodes is needed. The proposed approach has yielded a good estimation of network energy consumption. Furthermore, previous studies normally assume that battery energy levels of sensor nodes are the same. However, in a real network, battery quality is different, and the energy in each sensor node is a random variable. We provide a mathematical approximation and a standard deviation study for energy consumption, as well as a more in-depth study for network lifetime under random batter energy.
机译:能耗是无线传感器网络中的重要研究课题。使传感器节点进入睡眠状态是在电池供电的传感器节点中节省能源的最流行方法之一。关于睡眠技术的许多现有研究基于对传感器节点的部署的预先了解,例如,在目标感测领域中传感器节点的已知概率分布。因此,调度睡眠方案是否具有良好的性能主要取决于传感器节点的部署知识。在本文中,我们首先基于对基于群集的传感器网络中传感器节点部署的不正确了解,显示了系统性能指标的差异,包括能耗和网络寿命。通过分析研究,我们得出结论,差异非常大,不能忽略。因此,我们提出了一种无分布方法来研究能耗。在我们的方法中,不需要假设部署传感器节点的概率分布。所提出的方法已经很好地估计了网络能耗。此外,以前的研究通常假设传感器节点的电池能量水平相同。但是,在实际网络中,电池质量是不同的,并且每个传感器节点中的能量都是随机变量。我们提供了能量消耗的数学近似和标准偏差研究,以及在随机电池能量下网络寿命的更深入研究。

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