Research On Reliable Transmission Mechanism Of Key Data In Wireless Peer-to-Peer Networks Under Priority Code Preemption Strategy

The application based on the Internet of Things technology came into being with the rapid development of the Internet of Things technology.Wireless sensor network as the core infrastructure in IoT technology,its application scenarios are becoming more and more extensive,such as industrial fault point detection in industrial production,battlefield situation detection during wartime,and forest fire warning in forest fire prevention.A wireless sensor network is a wireless self-organizing network with data as the core and data sensing,collection and storage functions.Its network nodes are distributed in harsh environments and the resources carried by the nodes are limited.Due to the uncertainty of the monitoring environment,network nodes may be destroyed at any time,which greatly reduces the reliability of data in the network.Some key data in the network,such as the location information of the ignition point and the information of the fault point in the industry,are of vital importance to the decision maker.These data should be transmitted to the decision maker quickly and reliably.Therefore,it is very meaningful to study how to design and implement an efficient data collection protocol to improve the reliability and collection speed of key data in the network.Network coding technology is used to improve the reliability of data in wireless sensor networks because of its good performance.Since its introduction,many scholars have studied and improved it,among which the more representative research work is Growth Codes coding technology and its subsequent research work.The data collection protocol based on this type of coding technology makes the wireless sensor network have good performance in harsh environments.However,Growth Codes coding technology does not distinguish the importance of network data,but arbitrarily encodes and transmits key data in the network together with ordinary data.This may cause delays in the reception and decoding of key data and increase the risk of losing key data.In response to the above problems,this paper proposes a rapid data collection model and a redundant code source level probabilistic coding framework based on the Growth Codes coding technology to improve the efficiency and reliability of key data collection in wireless sensor networks,including the following work:(1)Aiming at the problem of low efficiency of key data collection caused by Growth Codes fair processing of all data on the network,this paper proposes a rapid data collection model.The model's network layering strategy allows nodes to roughly understand the location of the aggregation node,and the probabilistic routing strategy can also send the codeword to a level closer to the aggregation node with a higher probability,thereby reducing the number of invalid transmissions of the codeword and improving aggregation data recovery efficiency of the node.The priority-based preemptive coding method makes codewords containing key data have higher coding opportunities than ordinary codewords,which can increase the proportion of codewords containing key data in the overall codewords.Combining different coding preemption strategies,a data collection protocol based on probabilistic code preemption and a data collection protocol based on priority code preemption are proposed.Through simulation experiments,such protocols can provide good key data collection efficiency and maintain good data reliability.(2)Growth Codes uses a random exchange strategy in the node data exchange strategy,which may result in codewords containing more key data being exchanged away from the sink node.Therefore,we designed the probability forwarding table using neural network algorithm and genetic algorithm.Every time a node forwards a codeword,it will query the probability forwarding table,and exchange codewords with surrounding neighbor nodes with different probabilities according to the difference in the content of key data in the codeword.Codewords with higher key data content will be forwarded near the sink node with greater probability.The sink node can obtain higher-value code words,thereby improving the recovery efficiency of key data.(3)Aiming at the problem of decoding delay of key data collection at the end of fast data collection model in sparse network environment,this paper analyzes the reasons for its formation,and from the perspective of key code source coverage,proposes a redundant code source hierarchical probability coding framework.Compared with the rapid collection model,the improvement is that,on the basis of dividing the hierarchy,the remote code source has a probabilistic redundancy to the lower level node as its optional coding source data,this approach expands the influence range of remote key data,and reduce the limitation of code source distribution,thereby reducing the coding complexity and improving the efficiency of data collection.