Impact of Reference Nodes on Uncertainty in Hybrid Ad-Hoc Sensor Networks

Abstract

The uncertainty introduced by the use of low-cost sensors (LCSs) in ad-hoc sensor networks is an ongoing concern that can be alleviated at the network level through a hybrid solution that relies on the use of reference nodes and reputation-based trust management. As reference nodes impose a significant expense, it is important to minimize their number while maximizing their impact on the reduction of uncertainty. This article presents a multidimensional analytical model developed through simulations that helps in predicting the extent of the decrease in uncertainty caused by an increase in the fraction of reference nodes in hybrid ad-hoc networks. The model shows that the marginal benefit of introducing reference nodes is much higher for networks with small fractions of such nodes, and quickly reaches near-saturation at about 5% of reference nodes, across all aspects of uncertainty.