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Researchers Propose Novel Method for More Stable Wireless Sensor Networks

Sep 11, 2019     Email"> PrintText Size

Recently, a research group led by Prof. LIANG Wei and Prof. ZHENG Meng at Shenyang Institute of Automation (SIA) of the Chinese Academy of Sciences proposed a novel clustering protocol for cognitive radio sensor networks (CRSNs) which can significantly enhance the lifetime and stability of wireless sensor networks. The study was published in IEEE Internet of Things Journal 

With the proliferation of wireless technologies, wireless sensor networks and other wireless networks are coexisting over the licensed-free ISM 2.4GHz band. Consequently, the coexisting interference will sharply degrade the transmission performance of wireless sensor networks. 

CRSNs could be a potential solution that combines cognitive radio technology and wireless sensor networks. They allow sensor nodes to access the licensed bands with high quality dynamically, which significantly increases the transmission performance of wireless sensor networks. However, the dynamic spectrum leads the frequent variation in the topology of CRSNs and further heavy networking overhead.

Cluster-based management methods could effectively reduce the networking overhead. In this study, the researchers proposed for the first time a network stability aware clustering (NSAC) protocol for CRSNs.

In a NSAC, each node searches for the maximum edge biclique based on its neighbors and available channels. The weight of each node is calculated based on the remaining energy, the numbers of nodes and available common control channels in its maximum edge biclique. The node with the largest weight in the neighborhood will be selected as the cluster head, and the rest of nodes in the neighborhood will join the cluster as members.

As energy consumption and spectrum dynamics are sufficiently considered in the clustering process, network lifetime and network stability are noticeably enhanced.  

Extensive simulations showed that the proposed NSAC protocol for CRSNs obviously outperforms existing methods in the aspects of network stability and energy consumption.  

(Editor: LIU Jia)

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