Research On Key Techniques Based Energy Efficiency In Wireless Sensor Network

As the development of signal electronic product and computer electric system technology with wireless communication, low power consumption and high density of integration, the wireless sensor composed by sensor, wireless communication and internet has aroused extensive attention. The problem of sensor nodes and network energy-saving, which could be the decisive factor to affect the performance of wireless sensor networks, has become a hot topic of recent research. The paper focuses on three aspects as follows:network nodes positioning, network coverage, network routing. The three aspects are all around the network energy-saving issues. Based on them, we put forward corresponding models and algorithms, and conduct a theoretical proof and simulation analysis. The specific research contents of this paper are as follows:(1) A Multi-dimensional scaling iterative localization algorithm (RSSI-GA) proposed based on genetic algorithm RSSI. Considering the shortage of classic multi-dimensional calibration MDS-MAP algorithm in positioning accuracy and the computational complexity of matrix, the chapter has aroused genetic algorithm to design the RSSI-GA algorithm which composed diversity matrix directly according to the wireless signal strength values in multidimensional scaling technique. From the analysis of dissimilarity between individuals and the distance of geometric constraint relationship between each node, we use the unknown node as a parameter to establish optimization mathematical models, we also use genetic algorithm to find the optimal solution in the iterative parts, thus directly calculate the node coordinates. It is shown by the simulation results that the algorithm has a better performance in improving the positioning accuracy of the node.(2) A perception radius adaptive of coverage control mechanism has been presented. The paper studies sensor node selection problem in high-density conditions and presents a kind of adaptive perception radius of coverage control mechanism based on the problem of sensor network regional coverage. In the area of work node collection, each node has different sensor radius, each can adjust sensor effectively according to their location and their neighbors’status information, thereby reducing the coverage redundancy and improving network effectiveness. The nodes can greatly increase the overall network coverage, improve the efficient use of network energy and is superior to other existing model of the classic coverage in the aspect of coverage energy-saving.(3) A new protocol of Chain-cluster Routing Protocol (EBCRP) based on energy-balance has been presented. The chapter first analyzes several classic sub-cluster routing protocol. According to the problems such as unreasonable number of cluster heads, irrational distribution of cluster head position, as well as unreasonable cluster head election mechanism, we arouses chain-cluster routing protocol based on energy-balance (EBCRP). The main purpose is to divide the entire network into several rectangular regions, each region is considered a cluster, in accordance with step algorithm forming the routing chain in each cluster, and then select several cluster heads in the chain in order to take turns communicate with the base station to avoid cluster head’s earlier death, ensure that all nodes consume energy balanced. Simulation results show that EBCRP algorithm is superior to classical clustering routing protocol of the performance in the aspects of energy-saving, stability and extending network life cycle, etc.(4) We proposed an efficient energy cluster-based routing protocols (EECRP) based on PSO. The main idea is:a multi-hop cluster head transport data to the point of convergence. The network topology takes non-homogeneous sub-cluster ideas to solve the problem of hot zone, and consider status information of neighbors during the process of determining head nodes. We apply the Particle Swarm (PSO) algorithm to optimize the choice of cluster head to prevent the premature appearance of the blind nodes in order to achieve energy balance results. The simulation results illustrate that the algorithm has optimized the energy consumption in the network and extended network surviving times.(5) Three-dimensional plane routing protocols based on ant colony optimization algorithm. Facing the problem that wireless sensor network routing protocol lacking a universal performance and simultaneously meeting energy-efficient, expandability, robustness and fast convergence characteristic in wireless sensor network, based on ant colony algorithm, this chapter proposed an intelligent wireless sensor network routing protocol which has a strong universal agreement on the main body can be easily expanded for specific application, while the protocol is particularly suitable for three-dimensional space of wireless sensor network applications. The protocol has the characteristics of distributed computing, distributed information storage, low cost of routing communication and the little amount of information for local storage, low-power, energy load evenly and so on.The five research contents above are all around the issue of wireless sensor network energy-saving and illustrate the issue in different areas, aiming to detect the network energy-saving algorithms in the most important three aspects of network nodes positioning, network coverage, network routing. The simulation results show that the research results in the paper have better performance in improving the energy efficiency of network.