SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. In order to support fine-grained diagnostic analysis and optimize the performance level of the networks, the reconstruction of per-packet routing path is essential. However, in large-scale networks, the performance levels of the current path reconstruction method decline rapidly, with loss of links. An efficient approach to fully comprehend the complex internal behavior of network is through the reconstruction of the routing path of each received packet at the sink side. One of the most significant study in the field has been conducted on iPath, although the energy efficiency was absent in the study. Thus, the current study proposes SecPath, an energy efficient inference method that enables the reconstruction of the per-packet routing paths of large-scale networks, by providing a stable and efficient route to exchange messages between source and destination in a timely manner. This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. To achieve energy efficiency, it compresses the packet information by using GZIP tools in JAVA. SecPath is evaluated with several variations using 400 nodes in WSN deployments as well as large-scale simulations. The findings have demonstrated that SecPath surpassed other current approaches such as EEPMM. SecPath has accomplished low transmission overhead which it has reduced 13% of the energy consumption. Besides on the reimplementation also has gained significant reconstruction ratio compared with iPath.

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