Wireless Sensor Network Topology Control And Optimization

With the development of the Internet of Things, the interact between human society and nature change revolutionary.Internet of Things technology is deepening affect all aspects of social life, Due to the development of networking technology which undergoing change the fields of environmental monitoring,health care and education etc. Wireless sensor networks(WSNs) as the core support of Things technology, which been paying attention by many researchers. In recent years, research for WSNs has achieved fruitful results, but also still has lots problems need to solved.This paper from the practical background, through combine the complex network theory and characteristics of WSNs(The network topology control)to research and analysis the WSNs optimization. By establishing a more realistic network evolution model of sensor networks and energy consumption model and efficient algorithm to solve large-scale and time-consuming network optimization issues is provided. Through analysis the relationship between the performance of WSNs, we trying to find the optimal overall performance optimization method. The main contents are as follows:(1) Put forward a WSNs topology control and optimization model(CTC-AR) with adaptive nodes.WSNs is a kind of power-constrained network, so judicious power management and sensor scheduling can effectively extend network lifetime. To date, many approach have being researched. In this paper, we considered the connected target coverage with adjustable sensing range problem(CTC-AR) with the object of extend the network lifetime by scheduling the sensors into lots number of set covers,and each of them can maintain both connectivity and target coverage. Each sensor in the set covers have adjustable sensing range and we take into data aggregation. We mode the CTC-AR problem as the maximum set cover trees problem(MSCT), which is NP-complete. And the problem is formulated as the mixed-integer linearprogramming problem model(M-ILP) to maximizing the network lifetime.(2) Base on the mode we presents efficient heuristic connectivity tree algorithm(CGC-AR).As the time cost to solve M-ILP problem by CPLEX maybe high in practice, we develop a faster greedy approach based on M-ILP called Connected Greedy Cover with Adjustable Range algorithm(CGC-AR). Simulation results are presented to verify our approaches.(3) Put forward a comprehensive performance optimization model(C-POM).The performance optimization is one of the core issues in WSNs. The present study is mainly from two directions, the power control and the sleep scheduling. A well-designed network performance optimization method is not only close to the actual but also have good generality. There are many aspects which need to be studied further. In older to achieve a trade-off among the network comprehensive performance and the network survival time, in this paper, we use gain and costs to characterize the whole network performance, and the comprehensive performance optimization evaluation model(C-POEM) based on complex network theory is proposed.(4) Base on the gains and cost, we proposed high time optimization algorithm for the mode.Through analyzes the relationship of the sensor network performance, verify the effectiveness of the model.Additionally, we also give the relevant optimization algorithm, and this algorithm offers significant complexity reduction when applied in practical scenarios. Simulation results show that the typical WSNs have the best network average degree to making the network obtain maximum income.