Research On Nod's Power Consumption Based On Artificial Intelligence In Sensor Networks

Sensor networks is developed based on applications, which has such features as big scale, self-organized hop, no watching and no communicational infrastructure compared with traditional wireless communication networks. However, energy constraint becoming bottlenecks always restricts developments and applications in sensor networks.Increasing networks efficiency, decreasing nod's power consumption and prolonging network lifetime play a very important role on the research of sensor networks, which is the essence in this paper. To balance on networks power-efficiency and power-equation in routing paths is the main topic in this paper. Moreover, the guidance is by way of applying artificial intelligence technique, especially using mathematical models of neural networks as tools for analyzing sensor networks in the paper. We colligate and discuss researching issues at home and abroad about power consumption in warless sensor networks. Then we make a deep research on popular algorithms and protocols , design on hardware in each layer of OSI model, analyze the main reason on sensors nod's power consumption in both hardware layer and protocols layer on the promise of considering systematical structure of sensor networks.In this paper, we put the mathematical model for warless transmitting consumption forward by analyzing nod's inner structure, communicational way and coverage on account of impulsions on nod's consumption.we discuss and compare some typical Middle Access Control algorithms and protocols in sensor networks, analyze the present problems about power-saving algorithms, protocols and problem been not still dealt, which is all based on considering and analyzing key techniques in energy-saving, such as power-saving in single sensor, data fusion and power-saving algorithms in crossing layers.Conclusions and contributions are applying artificial intelligence technique to routing algorithms in sensor networks. Firstly, considering non-equation in networks' general energy in and non-reliable Quality of Service. Self-Organizing Map and Data Fusion algorithms-SOMDF is presented based on both neural networks models and data aggression. This algorithm can decrease data transmission on sensor nods and avoid the risk of data conflict and more power consumption. In addition, Dynamical Routing Selection strategy is put forth in the paper based on SOMDF algorithm. This Strategy can ensure reliability, stability, real time and balancing networks energy efficiency and equation in routing compared with traditional wireless networks, which has property of routing base on data. DRS divide routing paths into two types: one is Trunk Routing and another is Branch Routing according to Connectivity Evaluation Quality computed by SOMDF. Finally, in view of such properties as assembling and self-organizing of cluster routing algorithms in sensor networks, we apply Echo State Networks model in neural networks to cluster routing algorithms. Echo State Networks Routing Selection algorithm--ESNRS is specially designed for clustering in routing paths. ESNRS has short-term memory, which can decrease power in communicating and prolong the lifetime of networks.In order to measure merits and drawbacks, we evaluate and test SOMDF, DRS and ESNRS from converge, transmission delay, nod's power consumption and networks' energy equation.