Energy-efficient Data Collection Mechanism Research Based On Sleep Scheduling In Wireless Sensor Networks

An important application field of wireless sensor networks is data collection. In order to make the appropriate decisions, it need to analysis the data collected by the nodes to the base station. At the same time, the data collection technology is one of the important supporting technologies for the wireless sensor network. With the development of the technology of big data, data collection technology of wireless sensor network is gradually developing towards the direction of multi-source information, mass information and redundant collection. However, the computing, storage, communication and sensing capabilities of wireless sensor networks are limited, which is a big challenge for the efficiency of data collection. Data collection technology with energy efficiency as the primary consideration is becoming the focus of research in this field.In this thesis, the related works of data collection technology in wireless sensor networks are studied, and the advantages and disadvantages of the existing algorithms and techniques are analyzed. In order to reduce the energy consumption and balance the energy consumption, a cluster based data collection model is established. At the same time, to ensure network coverage and reduce the number of redundant nodes, the optimized deployment of static network is realized. The main research contents of this thesis are as follows:(1) Firstly, the basic characteristics, architecture, key technologies and applications of wireless sensor networks are introduced, and the research status of data collection technology is investigated, and we also classify the algorithms of data collection into certain types.(2) In order to solve the problem of redundant coverage and reduce the number of redundant nodes, this thesis introduces a type of coverage optimization algorithm based on the information of it’s neighbors. It will let the node go sleeping by judging whether it is redundant in algorithm. The experimental results and theoretical analysis show that the algorithm can effectively reduce the number of the redundant nodes and save the energy of the whole network.(3) Based on the k-means algorithm, the uniform size of a cluster of network model is constructed, and the energy consumption of network is analyzed. A data collection algorithm based on rotation of cluster head is designed in order to balance the energy consumption.(4) A type of discriminate algorithm on coverage redundancy based on the information of its neighbors is also introduced in this thesis. Each node calculates the coverage rate of its sensing area, depending on the locations of its neighbor nodes. If the coverage rate is beyond the threshold, the redundant node will go into sleeping mode to save energy. Experimental results show that the algorithm can effectively reduce the number of redundant nodes as well as the energy consumption of the whole network.