Performance of wireless sensor networks can be degraded by false error reports, which flood the network.

In this project, a method for valid error identification is being developed and applied to wireless sensor networks. By measuring the reported data against the expected data for a network node, a delta function data set can be computed. When matched to the expected pattern of behavior, the resulting data set, free of false data reports, provides a validated data base. Research outcomes include superior placement algorithms for wireless sensor network nodes, reducing error reporting and improving network management and performance.