Efficient parallel algorithms for dead sensor diagnosis and multiple access channels
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
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In wireless sensor networks, data from sensors has to be transported to a central server or sink. Since the sensors are power-constrained devices, the data is typically fused en route, and an aggregated report of fused information is finally available at the sink. It is important that information from as many sensors as possible be fused in order to increase the credibility of the aggregated report. However, in sensor networks there may be faulty sensors or even malicious intruders that generate and report misleading information. Thus, it is important to collect and fuse enough correct reports that agree with each other; this would enable nodes that perform fusion to detect and ignore the effects of the faulty reports. In this work, we propose a protocol called corroborative aggregation protocol (CAP), in which, each sensor that detects a report from its neighbor that contradicts its own findings generates its own report to dispute the faulty report. The idea is to increase the number of correct reports so as to effectively reduce the adverse effects of faulty reports. We show by simulations that CAP is effective in maintaining the credibility of the final fused content even if approximately 30% of sensors within a detecting zone are wrong about an event.