Power-saving Data-gathering Techniques For Wireless Sensor Networks Used In Detecting Temperature And Humidity

In recent years, energy conservation has become a very important content in national development strategy. The contradiction between China's energy supply and economic and social development is very conspicuous. Building energy consumption is very prominent. Energy-saving buildings have huge potential. Thus, detecting the temperature and humidity of buildings is particularly essential.At present, the main forms of information gathering at home and abroad are: wired and wireless. In the wired way, its integrated wiring needs large quantity of work and it is high cost. There are still other difficult problems for existing buildings, such as damage to the building appearance. Research and practice shows that the energy consumption detection products with wireless sensor network technology are most available. The project is suitable for a variety of existing buildings and new buildings. Wireless sensor networks have self-organizing ability and energy consumption monitoring can be implemented fast, conveniently and non-destructively. The application market has great potential.This paper intends to research a key issue on temperature and humidity detection system based on wireless sensor networks. The key issue is energy-saving data gathering. At present, some algorithms of energy-saving data gathering such as gathering algorithm based on minimum spanning tree, reduce the entire network energy consumption, but shorten the network life time. The reason is that in these algorithms, some hub nodes take too much data packet forwarding. It leads to premature depletion of battery power and even death. Therefore, this article comprehensively consider the energy needs to transfer data between network nodes, own nodes'residual energy, neighbor nodes'residual energy, the data gathering minimum routing hop. It also uses Dijkstra algorithm and introduces two weight functions. Then it proposes ratio weight gathering algorithm (Ratio-CEH), and sum weight gathering algorithm (Sum-CEH) based on factors such as energy consumption, residual energy and hops. The paper details the parameters'choice in two algorithms and the choice's impact to network life time and energy consumption, comparing with the PEDAP, PEDAP-PA and LET algorithms. Simulation results show that we can extend the network life time, reduce network latency and enable cost-effective energy consumption with adjusting the parameters of Ratio-CEH and Sum-CEH algorithms. Under certain conditions , the Ratio-CEH and Sum-CEH algorithms outperform PEDAP,PEDAP-PA and LET algorithms.The algorithms proposed in this paper can extend network life time as much as possible, reduce network latency and maintain energy consumption at a relatively low level. It has certain application worth.