An efficient and high-performance WSNs restoration algorithm for fault nodes based on FT in data aggregation scheduling

• Introducing the fat tree structure to study the performance of wireless sensor fusion scheduling. • A unified shielding algorithm has been proposed for all types of faulty nodes. • The fat tree constructed in this article is the collection of all shortest path trees. • Using network topology technology to perform different pruning schemes on fat trees, generate aggregation trees, and maintain the original network performance. • Utilize the information recorded in the nodes during the construction process of the fat tree to achieve rapid reconstruction of the aggregation tree. In wireless sensor networks(WSNs), data aggregation effectively reduces network traffic, thereby reducing energy consumption and improving network life cycle. Nevertheless, in the process of data aggregation scheduling, if there are fault nodes, the data quality collected by the whole network will decline, and the network performance will decrease, even posing a threat to network security or causing network paralysis. Thus, an efficient and high-performance WSNs restoration algorithm is proposed based on fat tree(FT), which is referred to as the EPRA-FT algorithm. And our goal is to improve the universality, efficiency, and performance retention of the algorithm. Previously, we have conducted a range of the relevant researches on performance improvement of WSNs aggregation scheduling by adopting FT structure, and some successful results have been obtained. On the basis of these results, for the EPRA-FT algorithm, first and foremost, the relationship among nodes is comprehensively recorded in FT construction process. Then, fault nodes are shielded by deleting the known nodes in aggregation tree. Finally, the local reconfiguration of aggregation tree is completed quickly and efficiently. Meanwhile, the aggregation scheduling performance of the original network is maintained to the maximum extent. The feasibility and superiority of our proposed EPRA-FT algorithm are proved by simulation experiments.