Multi-granular Topology-based WSN Stepwise Refinement Provenance Method

The Wireless Sensor Network(WSN)has many kinds of nodes which are small size,low power consumption,and are easily influenced by the external environment.Therefore,it is usually necessary to evaluate the credibility of data received by the base station(BS).Provenance in WSN records the generation of data and its transmission process.And it is an important basis for evaluating the credibility of received data.In large-scale WSNs,with the number of data transmission hops increasing,the Provenance data volume will also increase.This will not only consume the limited energy of the nodes,but also cause the capacity of the data packets to be overloaded under certain extreme conditions.The staff proposed Provenance segmented transmission method.However,such a method required segmentation of Provenance to fully arrive at the BS before decoding.In view of this,in order to solve the shortcomings of the traditional segmentation method,this thesis proposed a multi-granular topology graph based WSN stepwise refinement method.The basic idea is: Divide the WSN topology map into some abstract topological maps according to some rules.And then transmit the Provenance segmentation in different granularity.In this way,the BS can decode Provenance at coarser granularity based on Provenance segments which were already received,and then use subsequent segments to incrementally refine the granularity of the decoding,until getting accurate results.The main work of this article is as follows:(1)We proposed a multi-granularity topological map-based WSN stepwise refinement Provenance method.First,the information entropy is used to define the equivalence relationship.Then,through retrieving the mutual information between nodes,the topology of the WSN is recursively divided into multiple topological abstract graphs with different granularities.(2)In the multi-granularity abstract topology map of WSN,transmitting Provenance from coarse to fine step-by-step,incremental.Design and implement a dictionary compression method to compress Provenance based on multi-granular topology.As a result,improving the Provenance's average compression ratio.At the same time,we also discuss the processing method when the WSN topology changes dynamically.(3)The TOSSIM simulation and the power simulation based on PowerTOSSIMz were completed under the TinyOS-2.1.2 system,and the corresponding hardware networking experiment was completed on the ZigBee hardware node.Both theoretical analysis and experimental data show that: compared with the traditional segmentation method,the method of this thesis can make up the insufficiency of the existing provenance segmented transmission method,and has a higher compression ratio and can effectively reduce energy consumption.