Reserch On Key Technologies Of Perceptual Layer Of The Internet Of Things

The Internet of things is a revolutionary development following the computer, Internet and mobile communication. In recent years, it is widely used in industrial monitoring, health care, intelligent traffic, and so on. The research on the Internet of things has been increasingly attached great importance by governments, academic circles and industry, and many new technologies continue to appear. Among them, as two key technologies, WSN and RFID play irreplaceable roles in the system of the Internet of things.This thesis aims at the research on the perceptual layer key technologies, i.e. the routing protocol of WSN and the anti-collision algorithm of RFID system. The main works and result are as follows:Firstly, the position and action of the perceptual layer are described in the Internet of things, and the WSN and RFID technologies are respectively introduced. Then the routing protocols of WSN and anti-collision algorithm of RFID system are studied.Secondly, based on analyzing EEUC algorithm, an energy-balanced uneven clustering routing algorithm (EBUC) is designed, which borrows cluster heads generation idea of LEACH and uses the factor of residual energy in order to improve the election mechanism of candidate cluster heads. The concept of independent nodes to reduce some cluster heads’ loads and uses different priorities for optimizing inter-cluster route are introduced. Simulation results show that EBUC can efficiently prolong the WSN lifetime.Thirdly, a novel ID prediction anti-collision algorithm (NIPA) is proposed. On the one hand the algorithm can read all tags When the RFID system detects that only two-bit data collides. On the other hand it uses the known information remembered by the feedback tags’ information, in order to reduce the number of data traffic. Simulation results show that NIPA can shorten the time of identifying all tags and reduce data transmission redundancy.