Research On Provenance Compression Algorithm Based On Hierarchical View In WSN

Wireless communication technology,the sensor technology and embedded technology make unceasing progress so that the sensor nodes develop fastly,thus the wireless sensor network(WSN)composed of micro sensors has been rapid popularization.In WSN,the sensor nodes gather all kinds of object information sent to the base station(BS)via wireless communication.However,due to the diversity of the environment and a large number of sensor types involved,it is essential to evaluate the credibility of the data.In order to ensure that the information used for the key decision is trustworthy,a data provenance allows the BS to trace the source and forwarding/aggregating nodes of an individual data packet since its generation.On account of the provenance size expanding rapidly with the number of the hops increasing,the provenance is generally divided into smaller blocks and then transmitted each block independently.As to the known provenance schemes,concerning low compression ratio and reconstructing a provenance that requires all the provenance blocks arrived at the BS precisely,the paper presents an incremental transmission and gradual reconstruction provenance scheme.By using the hierarchical clustering to manage the WSN and the prime number factorization technique,the BS can reconstruct a provenance from a coarse-grained one to a fine-grained one,which also achieves a higher provenance compression rate.Both theoretical analyses and experimental results show that our method has a higher compression ratio when compared to the known block based transmission approaches,and therefore it can conserve more energy and achieve better robustness due to incremental transmission.