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

Wireless sensor network is one of the supportive technologies of perceptual layer,while the protocol of routing determines the property of the sensor network.As for sensor network,life period and data transmission delay are the most significant problems.Aiming at these key factors,the first part of this paper proposes the PEGASIS_BMST algorithm,which is based on PEGASIS algorithm.In order to reduce energy consumption and data transmission delay,the routing topology of the PEGASIS_BMST algorithm is mainly based on the minimum spanning tree to minimize the sum of entire network nodes' total paths.In addition,the PEGASIS_BMST algorithm also combines the idea of stratification and proposes a cluster election strategy which is considering the residual energy of nodes and distance from the base station.Through the adoption of this strategy,the energy consumption load has been balanced.By the theory and simulation experiments,it has been proved that PEGASIS_BMST algorithm can improve the network life period effectively and reduce delay of data transmission.Radio frequency identification technology is another key technology of perceptual layer.Compared with other traditional identification technologies,radio frequency identification has great advantages.Its non-contact identification,high accuracy,strong adaptability and other advantages make the rapid development of radio frequency identification.The Anti-collision algorithm is the key technology of radio frequency identification technology.The merits of the anti-collision algorithm determine the performance of the system to a large extent.The second part of this paper focuses on a series of ALOHA algorithms and proposes a new grouping algorithm named EDFSA which is based on DFSA algorithm.The main point of EDFSA algorithm is that it can be self-sorting by labeling the energy size.The simulation results show that EDFSA algorithm can effectively improve the efficiency of the system.