Research On Reliable Data Collection Mechanism In The Wireless Peer-to-peer Network Based On Effective Data Filtering Strategy With A Sectional Configured Model

The wireless sensor network completes data monitoring and collection tasks through a large number of sensor nodes in a certain area,which are equipped with wireless communication technology.WSN has a wide range of applications and great potential in various fields.It can be said that the WSN has opened up many new possibilities for emerging applications in the field of event tracking and monitoring.Correspondingly,because it is often deployed in harsh environments and lacks human involvement,the WSN faces many challenges and constraints.Ensuring data collection reliability and data recovery efficiency of the WSN,and designing reliable data collection schemes are very meaningful for its improvement in applications.Numerous nodes generate a large amount of data,and the broadcast characteristic makes redundant data widely exist in the WSN.Network coding technology can not only reduce data redundancy and save bandwidth consumption,but also ensure the survivability of network data.Among them,a coding scheme called Growth Codes,which is a representative scheme for improving data persistence in disaster network,using the means of gradually increasing the amount of data participating in coding and random data distributions.However,in the later period,many unavoidably redundant codewords(encoding packets containing only recovered data)slow down the data collection efficiency.In addition,the encoded data that cannot be decoded immediately also affects the data recovery efficiency.Focusing on the above issues that affect data collection performance,in this paper,two improved data collecting protocols based on the Growth codes,SCGC and GCPDP are proposed.These protocols are designed from the perspective of reducing redundant codewords that affect data collection performance and ensuring intermediate recovery performance during data collection.The main works of this paper includes:(1)This article analyzed the causes of the decreased data recovering efficiency in the later period of data collection.From the perspective of reducing the probability of forwarding the redundant codewords which only consisted by recovered data to the sink,a data collection protocol named SCGC(a Sectional Configured data collection strategy based on the Growth codes)is proposed.In the sectional configured network model adopted in this protocol,the neighbor nodes of the sink are set as cache nodes to filter the redundant codewords.Further,the cache nodes scheduling mechanism and the information update strategy can effectively ensure the performance of filtering as well as reduce conflicts.Simulation experiments prove that this protocol can effectively improve the data recovering efficiency in the later period of data collection.(2)The energy consumption and stability of sensor nodes are also key to the practical application of the WSN.If the network is configured too much,it will cause the nodes failure in advance and reduce the whole network's lifetime.In harsh environment such as disaster scenarios,the nodes can be easily damaged.In this paper,starting from reducing the energy consumption of cache nodes,the constraints of the number of cache nodes and the information update cycle are proposed.The constraints are designed with the degree distribution based on Growth codes and the statistics of forwarded data packets.While ensuring the filtering performance of cache nodes,the unnecessary consumption of update is well reduced.Through theoretical analysis,mathematical derivation and experiments simulation,the constraints can guarantee the stability of the entire network,further verifying the reliability of the SCGC data collection protocol.(3)In sparse networks,due to the low density of sensor nodes,it is easier to cause the uneven data distribution during the completely random data forwarding process,which lengthens the time of data to forward to the sink.In Growth codes,the degree of data packet increases with time,so the longer forwarding time results in more appearance of codewords which cannot be decoded immediately.Due to the increased decode difficulty,these codewords will affect the overall data collection efficiency.Focus on this problem,a data collection protocol GCPDP(a Growth codes based data collection strategy with Partial Decoding Protocol)is proposed.A pseudo-random data exchange strategy is designed to reduce the number of codewords with higher decode difficulty.An improved partial decoding algorithm is adopted to increasing the decoding efficiency of the sink.Simulation experiments show that,in sparse networks,the GCPDP performs well in terms of overall data collection efficiency and intermediate decoding performance.Particularly,simulation experiments ported to SCGC also show that this protocol framework is extensible.