School of Information Science and Engineering, Fujian University of Technology, and Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fuzhou, China.
Department of Computer Science and Software Engineering, Swinburne University of Technology, Hawthorn, Australia.
PLoS One. 2018 May 15;13(5):e0196705. doi: 10.1371/journal.pone.0196705. eCollection 2018.
Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.
数据收集是无线可视传感器网络 (WVSN) 的基本任务。定向天线和可视数据的特点使得 WVSN 比传统的无线传感器网络 (WSN) 更为复杂。虚拟骨干网是一种能够构建集群的技术。与聚合操作相关的版本也被称为虚拟骨干树。在大多数现有文献中，主要关注点是现有方法通常忽略局部平衡问题的集群构建效率。为了填补这一空白，本文提出了一种用于 WVSN 的基于定向虚拟骨干的数据聚合方案 (DVBDAS)。此外，还提出了一个称为能量消耗密度的度量标准，用于评估基于簇的构建问题中结果的充分性。此外，通过考虑局部平衡因素来提出定向虚拟骨干构建方案。此外，还利用相关的网络编码机制来构建 DVBDAS。最后，对所提出的 DVBDAS 进行了理论分析和仿真，以评估其性能。实验结果证明，与现有方法相比，所提出的 DVBDAS 在能量保存和网络寿命延长方面都具有更高的性能。
