Data Provenance Compression Using Cluster Based Arithmetic Coding In Wireless Sensor Networks

In wireless sensor networks, data provenance is one of the important basis for assessing the trustworthiness of the data. Provenance records the whole nodes on the path from source node to the base station of a data packet and the operation of these nodes. Therefore, the size of Provenance will expand rapidly with the increase of the length of the data packet transmission path. At present, we have studied traditional arithmetic coding compression method, but the low compression efficiency and large computational load of BS is still a major problem.Concerning the low compression efficiency of the traditional arithmetic coding and the resource constrained in WSN, the paper presents a cluster-based arithmetic encoding method, which is lossless. By using the cluster to manage the WSN, it yields a higher data compression ratio and then effectively reduces the load of BS.The main work of this paper includes the following:(1) On the basis of the organization WSN clustering methods, the use of distributed arithmetic coding based on multi-level traceability data compression method, to obtain a higher compression ratio traceability data, and can effectively reduce the computational load of BS.(2)For any given WSN, the relationship between the different clustering methods and the provenance’s size is given and the existence of the optimal clustering size is proved.(3) In the implementation of the compression process, the use of lightweight methods to protect the safety of the Provenance and save energy.(4) Through theoretical analysis, experimental simulation and hardware experiment to examine the performance of the method and verify its feasibility.