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Provenance Compression Using Packet-Path-Index Differences in Wireless Sensor Networks

机译:无线传感器网络中使用分组路径索引差异的源压缩

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In wireless sensor networks (WSNs), provenance is critical for assessing the trustworthiness of data acquired and forwarded by sensor nodes, detecting early signs of attacks, etc. However, the provenance size expands rapidly with increases in the number of packet transmission hops. Among the existing provenance schemes, the dictionary based provenance scheme (DP) achieves the highest provenance compression rate. However, the major drawback of the DP scheme is that it is sensitive to the WSN's topology changes, which cannot be used in the WSNs with rapid topology changes. To overcome such a drawback and achieve a higher compression rate, we propose a path index differences based provenance scheme, in which we first establish backbone paths along the gradient direction, and then we devise a Truncation Hamming Distance (THD) based method to eliminate the backbone paths with high similarity and build the path dictionaries for the selected backbone paths of low similarity. With the support of such dictionaries, a new path is encoded by the index of a similar path in the dictionary together with the differences between them, which makes the size of the provenance stably compressed. Compared to the DP scheme, the simulation and experimental results show that our scheme can achieve a higher provenance compression ratio even if the topology structure of the WSN is not stable.
机译:在无线传感器网络(WSN)中,出处对于评估传感器节点获取和转发的数据的可信赖性,检测攻击的早期迹象等至关重要。但是,出处的大小随着数据包传输跳数的增加而迅速扩展。在现有的出处方案中,基于字典的出处方案(DP)实现了最高的出处压缩率。但是,DP方案的主要缺点是它对WSN的拓扑更改敏感,不能在具有快速拓扑更改的WSN中使用。为了克服这种缺点并获得更高的压缩率,我们提出了一种基于路径索引差异的出处方案,该方案中,我们首先沿梯度方向建立主干路径,然后设计出一种基于截断汉明距离(THD)的方法来消除这种情况。具有高相似性的主干路径,并为所选的低相似性主干路径构建路径字典。在这样的词典的支持下,新路径由字典中相似路径的索引以及它们之间的差异来编码,从而稳定地压缩了出处的大小。与DP方案相比,仿真和实验结果表明,即使WSN的拓扑结构不稳定,我们的方案也可以实现更高的出处压缩率。

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