论文标题
关于无线传感器网络的布尔 - 波森群集模型的覆盖范围性能
On the Coverage Performance of Boolean-Poisson Cluster Models for Wireless Sensor Networks
论文作者
论文摘要
在本文中，我们考虑了无线传感器网络（WSN），其中传感器节点在部署中显示了聚类。我们通过布尔泊松泊松簇模型（BPCM）对此类WSN的覆盖区域进行建模，其中传感器节点的位置根据泊松群集过程（PCP），并且每个传感器围绕它具有独立的传感范围。我们考虑PCP的两种变体，尤其是\ Matern和Thomas群集过程，以形成布尔\ matern和Thomas群集模型。我们首先得出这些模型的容量功能。使用派生的表达式，我们计算事件的感应概率，并将其与由布尔泊松模型建模的WSN的感应概率进行比较，在该模型中，根据泊松点过程部署了传感器。我们还得出了每个群集收集其所有传感器数据的数据所需的功率。我们表明，与布尔泊森WSN相比，BPCM WSN的功率要求较小，但其覆盖范围较低，从而导致人均功率需求和传感性能之间的权衡。带有所需聚类的集群过程可以提供更好的覆盖范围，同时保持低功率要求。
In this paper, we consider wireless sensor networks (WSNs) with sensor nodes exhibiting clustering in their deployment. We model the coverage region of such WSNs by Boolean Poisson cluster models (BPCM) where sensors nodes' location is according to a Poisson cluster process (PCP) and each sensor has an independent sensing range around it. We consider two variants of PCP, in particular \matern and Thomas cluster process to form Boolean \matern and Thomas cluster models. We first derive the capacity functional of these models. Using the derived expressions, we compute the sensing probability of an event and compare it with sensing probability of a WSN modeled by a Boolean Poisson model where sensors are deployed according to a Poisson point process. We also derive the power required for each cluster to collect data from all of its sensors for the three considered WSNs. We show that a BPCM WSN has less power requirement in comparison to the Boolean Poisson WSN, but it suffers from lower coverage, leading to a trade-off between per-cluster power requirement and the sensing performance. A cluster process with desired clustering may provide better coverage while maintaining low power requirements.
