Multiple cognitive nodes in wireless sensor networks

F. Aalamifar, P. A. Khoozani, M. Ibnkahla
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引用次数: 6

Abstract

Recently, cognitive wireless sensor networks (CWSN) have been proposed to enhance the overall functionality of WSNs based on application needs. Cognition refers to the process of making decisions and acting based on the network conditions in order to achieve end-to-end goals of the network. In the previously proposed architecture, a new node - Cognitive Node (CN)-, which is responsible for managing the network, was introduced to the network. Since WSNs normally consist of a huge number of Sensor Nodes (SNs), there is a high demand to have more than one CN. In this paper, challenges of adding multiple CNs are investigated and a new architecture is proposed. Then, the proposed architecture is evaluated by implementing it with CC2430 boards (Texas Instrument boards). The results of our experiments showed that the proposed architecture can function more efficiently by increasing the number of SNs in each subclass.
无线传感器网络中的多认知节点
近年来,认知无线传感器网络(cognitive wireless sensor network, CWSN)被提出,基于应用需求增强无线传感器网络的整体功能。认知是指为了实现网络端到端的目标,根据网络条件做出决策和行动的过程。在之前提出的体系结构中,在网络中引入了一个负责管理网络的新节点——认知节点(CN)。由于WSNs通常由大量的传感器节点(SNs)组成,因此对多个CN的要求很高。本文研究了增加多个神经网络所面临的挑战,并提出了一种新的神经网络结构。然后,通过在CC2430板(德州仪器板)上实现对所提出的架构进行了评估。我们的实验结果表明,通过增加每个子类中的SNs数量,所提出的架构可以更有效地运行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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