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    Fu Xiuwen, Li Wenfeng, Duan Ying. Invulnerability of Clustering Wireless Sensor Network Towards Cascading Failures[J]. Journal of Computer Research and Development, 2016, 53(12): 2882-2892. DOI: 10.7544/issn1000-1239.2016.20150455
    Citation: Fu Xiuwen, Li Wenfeng, Duan Ying. Invulnerability of Clustering Wireless Sensor Network Towards Cascading Failures[J]. Journal of Computer Research and Development, 2016, 53(12): 2882-2892. DOI: 10.7544/issn1000-1239.2016.20150455

    Invulnerability of Clustering Wireless Sensor Network Towards Cascading Failures

    • Current researches of cascading failures of wireless sensor network (WSN) mainly focus on peer-to-peer (P2P) structure. However, in real scenarios most of sensor networks always collect and deliver environmental data via clustering structure. Therefore, through observing the heterogeneity of connections in clustered networks, we construct a cascading failure model of wireless sensor network by introducing the concept of “sensing load” and “relay load”. Besides that, we discuss the relevant features between key parameters of cascading model and invulnerability of two typical clustering topologies (i.e., scale-free topology and random topology). In order to constrain the scale of cascading failures, we also discuss how to select cluster heads to enlarge their capacity to achieve this purpose. The simulation and theoretical results show that the network invulnerability is negatively correlated to the proportion of cluster heads p and positively correlated to the allocation coefficient A. When adjustment coefficient α=1, the invulnerability of the network is optimized. When adjustment coefficient α<1, choosing cluster heads with fewer cluster-cluster connections is a more efficient way to enhance the network invulnerability. When adjustment coefficient α>1, choosing cluster heads with more cluster-cluster connections is more cost-effective. When adjustment coefficient α=1, the scale of cascading failures is not related to the selecting schemes of cluster heads.
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