The Research Of Anti-monitoring Algorithm For Anisotropic Sensor Networks

As a combination of information sensoring, data processing, GPS localization and network communication, wireless sensor networks have a various application perspective in environment and military monitoring, earth quake and climate forecast,exploration for underground, deep water and outer space and other applications.External uncertaint environment often leads to hundreds of sensors shall be deployed to work together, so the large-scale sensor networks research is gradually aroused widespread interests and considered a challenging research topic of this century.The traditional academic researches start from the sensor nodes,focus on the researches of clustering algorithms,routing protocols,coverage and data aggregation techniques for wireless sensor network.This paper focuses on the mobile object, and hopes to find a path with most minimal risks to the destination for the mobile object. The anti-monitoring research of wireless sensor networks is a novel topic, although there are already some researchers having paid attention to it, but the researches on it is still remaining in the developing stage and there are not many documents and reports presented in this area. So it's worth of deep studying.To effectively solve the anti-monitoring problem for sensor networks,after analyzing several traditional typical anti-monitring technologies and pointing out their drawbacks, this paper proposed a new exposure model which can be used to estimate the risk approximately when a mobile object is moving along a path to traverse the sensory field deployed with lots of mobile anisotropic sensor nodes.And based on the newly proposed exposure model,a novel decision making algorithm is designed by combing with the anisotropic Voronoi tessellation schemes and the A* heuristic algorithm, which guarantees the mobile object can select a suitable path with approximately minimal risk to travel across the mobile anisotropic sensory field. Using Java language, a simulation experimental platform is designed to graphicly demonstrate the simulation of sensor distribution and the anti-monitoring path of the mobile object driven by different algorithm.At the same time, the program is capable of adjusting the parameters of the anti-monitoring algorithms to analyze the performance in all aspects.Through these experiments,an evaluation of these algorihms was made and the research results were summeraized.Theoretical analyses and simulation results show that this approach has good anti-monitoring performance.