Wireless sensing technology has paved the way for the cost‐effective deployment of dense networks of sensing transducers within large structural systems. By leveraging the embedded computing power residing within networks of wireless sensors, it has been shown that powerful data analyses can be performed autonomously and in‐network, without the need for central data processing. In this study, the power and flexibility of agent‐based data processing in the wireless structural monitoring environment is illuminated through the application of market‐based techniques to in‐network mode shape estimation. Specifically, by drawing on previous wireless sensor work in both decentralized frequency domain decomposition (FDD) and market‐based resource allocation, an algorithm derived from free‐market principles is developed through which an agent‐based wireless sensor network can autonomously and optimally shift emphasis between improving the accuracy of its mode shape calculations and reducing its dependency on any of the traditional limitations of wireless sensor networks: processing time, storage capacity, and power consumption. The developed algorithm is validated by estimating mode shapes using a network of wireless sensors deployed on the mezzanine balcony of Hill Auditorium located at the University of Michigan. Copyright © 2010 John Wiley & Sons, Ltd.