Adaptive Localization Method for Abnormal Nodes in Wireless Sensor Networks Based on Simulated Parallel Ant Colony Algorithm
Due to the large number of nodes in wireless sensor networks,there is a problem of locating fewer abnormal nodes in the adaptive localization process of abnormal nodes.A wireless sensor network anomaly node adaptive localization method based on simulated parallel ant colony algorithm is proposed to address the above issues.Extracted the raw data of abnormal nodes from the network,and the data attributes of abnormal nodes are analyzed in detail.Based on the parsed data attributes,utilized the optimization search characteristics of ant colony algorithm,combined with the idea of parallel computing,a parallel ant colony algorithm model is established,the cooperative is simulated and the behavior of ants in the process of searching for food is optimizated,the parallel ant colony algorithm is run,and the estimated coordinate values of abnormal nodes is obtained,the adaptive localization of nodes is implemented.The experimental results show that this method can locate multiple abnormal nodes in complex network environments and multiple types of anomalies,enhancing the robustness and adaptability of the localization method.
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