Collecting data in ad-hoc networks with reduced uncertainty

We consider the data gathering problem in wireless ad-hoc networks where a data mule traverses a set of sensors, each with vital information on its surrounding, and collects their data. The mule goal is to collect as much information as possible thereby reducing the information uncertainty but in the same time avoid visiting some of the nodes to minimize its travel distance. We study the problem when the mule travels over a tree or a tour and propose a 3-approximation algorithm that minimizes both the information uncertainty and travel distance. We also show the applicability of our approach for solving data collection problems in varying domains such as temperature monitoring, surveillance systems and sensor placement. Simulation results show that the proposed solution converges to the optimal for varying set of topologies, such as grids, stars, linear and random networks.