CSR-IM: Compressed Sensing Routing-Control- Method With Intelligent Migration-Mechanism Based on Sensing Cloud-Computing

• Main Authors: Zeyu Sun, Jun Liu, Zhixian Li, Tian Wang, Zhijian Wang, Fuqian Jia, Chunxiao Lai
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Intelligent migration-mechanism; sensing cloud-computing; routing-control-method; compressed sensing
• Online Access: https://ieeexplore.ieee.org/document/8981877/

Considering the event-based WSNs routing, the frequent changes of topology may result to the large energy costs in the whole network. Therefore, this paper proposes a Compressed Sensing Routing-control-method with Intelligent Migration-mechanism based on Sensing Cloud-computing (CSR-IM). First, the method gives a determining the moving speed and position of the target node through compressed sensing theory, and at the same time, it gives the lower bound calculation process of the target node state estimation value at k+1 time by the probability knowledge. Second, with the purpose of reducing the network load, the routing tree with the center of fog nodes is established to obtain the data in the route effectively and optimize the data aggregation routing process, and then energy cost of the whole network is balanced. Finally, the simulation experiments show that method of this paper (CSR-IM) and other algorithms have improved the average data aggregation rate by 8.19%, and the average network coverage has increased by 12.65%, which proves that the proposed algorithm is effective and practical.