A fast tree-search algorithm for joint leak detection and localisation using surface-borne ultrasonic acoustic signals is developed through a wireless sensor network. Owing to environmental noise and multipath fading of ultrasonic signals, false sensor observations are frequent in the observation data. The problem is modelled as a Bayesian inference model and the maximum a posteriori solution is approximated through a tree-search structure. The algorithm initially divides the area into large cells and approximates the observation likelihood function over these large cells. In a tree structure, a large cell with high likelihood is divided into smaller cells and the tree is expanded until the required estimation precision is obtained. Simulation and experimental results reveal advantages of the proposed technique in terms of estimation error and convergence speed in comparison with other conventional Bayesian techniques such as particle filtering.
Link layer network coding (LLNC) promises to provide high throughput in relay networks through combining packets at the relays and trading communication for computation. The emerging area of physical layer network coding (PLNC) exploits the electromagnetic nature of signals and eliminates the need for addition at the packet level, while making signal design and coding schemes adaptable to the channel conditions. Although network coding has been extensively studied recently, physical layer network coding has not received the attention it deserves. Several recent works introduced the pollution attack at the network layer; however, the network performance at the physical layer with pollution attacks has not been evaluated before. The main challenge with the pollution attack involves propagation of the corrupted packets in an epidemic manner, which degrades performance of the network. As PLNC schemes boost up the network throughput, a thorough study evaluating this superiority to the LLNC scheme in presence of an intruder is necessary. The robustness of both schemes towards an attack have been studied in this article.
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