Study On Wireless Sensor Networks For Environment Monitoring

Wireless sensor networks (WSNs) have become one of the important research fields in the world. It has a wide-range application background, especially in martial applications and environment monitoring due to special limitation of target environmental area.The key techniques and design methods of WSNs are researched in this paper, and a solution of an application-oriented WSN system is designed and constructed with routine protocols and algorithms, which is tested in our lab and used in the project of"wireless gas-meter reading system".In this paper, the main researches and results are listed as follows:1 An application-oriented WSN system model based on integration of WSN techniques and application requirements is provided with analyses of both requirements of each function module and principle of module design. This framework system is centered on the WSN techniques with flexibility, maintainability, expansibility and transportability due to the modularized and open structure.2 The network topology, which plays an important role in energy efficiency, shall be in consideration when WSN nodes are organized into wireless networks. In this paper, to construct network topology of the WSN system, we develop a set of rules of the random topology management (RTMR), which strengthens spreadability and connectivity of the network by dividing the network nodes into some subsets. And by applying modify subset rule (MSR) some isolate nodes can be avoided. Furthermore, the relations of node covering density, net covering density, the number of subsets and nodes are deduced and specified. Simulation results show that it can fitly satisfy the application requirements of WSN used in environment monitoring:①Energy saving is made with satisfactions of spreadability and connectivity while the sensors'accurate position and communication radius are unknown.②The RTMR decreases system outgoings with each working node knowing the least hops to the sink node.③Covering density can be adjusted dynamically by modifying parameter k.④This scheduling algorithm has homeostatic mechanism to time non-synchronization.⑤This algorithm is easily implementary.3 According to the changing regularity of node energy and net energy, with integration of ant colony optimization (ACO) algorithm, an ACO routine protocol base...