Routing Algorithm Base On Principal Component Analysis Theory For WSN

Recent technological advances have enabled the development of low-cost, low-power and multifunctional wireless sensor network (WSN). Sensor nodes have more and more small size, powerful microcontrollers, and the embedded system has improved constantly. Utilizing the limited energy and resource fully, collecting measurement data, transmitting the effective data in sensor nodes, become a hot research field. By efficiency of routing protocols, WSN creates proper network topology, such as cluster structure. Proper network topology not only can effectively reduce the overall transmission distance, improve the efficiency of transmission, but also establish foundation for data-collection, data-gathering, time-synchronizing, prolonging network lifecycle with saving nodes' energy. Measurement data gathering is important the same as routing algorithms in WSN. Available data-gathering also have the better adaptability and lower energy consumption in data transmission, moreover the base station can recover the approximate measurement data, which prolongs network lifecycle with saving nodes' energy.This dissertation analyses clustering routing algorithms and data-gathering algorithms by using Principal Component Analysis. This paper introduce related concepts, algorithm design goal, characteristics and challenges, protocol systems, application of problem areas, compare some existing routing algorithms characters. Then, This paper introduce Principal Component Analysis theory, give the relation between K-mean and Principal Component Analysis algorithm, describe preliminary studies on K-means algorithm in WSN application. We propose PCA-Guided Routing Algorithm Model, including the network model, the energy consumption model, PCA-Guided Clustering Model etc. Through comparison of performance simulation about LEACH and the PCA-Guided Routing Algorithm, the result indicates the algorithm caused equality of the energy consumption in the network node, the network topology and the cluster head nodes' distribution is more reasonable. So the algorithm prolongs the network lifetime and improves the network compatibility. Next part introduces data-gathering technology, PCA-Guided Data Aggregating Model, analyses application under single-layer and multi-layer conditions. The simulation result indicates that PCA-Guided Data-aggregating algorithm reduce the data transmission and ensure the accuracy of data transmission.Finally, we give some conclusions and outline a few directions for future research.