期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
期号：ICCSTAR
页码：166
出版社：S&S Publications
摘要：Wireless sensor networks (WSNs) often suffer from the disrupted connectivity due to unpredictablewireless channels, early depletion of node energy, and physical tampering by hostile users. The existence of adisconnected segment of the network referred to as network cut, leads to data loss, wasted power consumption, andcongestion in the WSN. However, existing approaches to network cut detection in the WSN rely on the assumption thata node or a link either works normally or fails, without considering the uncertain and random features of wireless linksin the WSN. In this paper, we extend the notion of the network cut based on the realistic wireless channel model.Furthermore, we formulate the problem of minimizing the normalized cut (Ncut) with critical nodes, considering thequality of wireless links, degree weights, and different priorities of sensor nodes. Then, we propose a network cutidentification algorithm and dominant eigenvector computation algorithm that efficiently identify multiple network cutsby computing multiple Eigen values and eigenvectors according to a given parameter of eigen value gap. Extensivesimulations are conducted to examine the effectiveness and robustness of the proposed approach. The results show thatthe proposed method strikes a balance between minimizing the Ncut objective and the degree of disconnection ofcritical nodes and achieves a better performance than existing algorithm.
