Stability and delay constraints have significant impact on the design and operation of wireless sensor networks. In this paper, we propose a closed architecture for data sampling in wireless sensor networks. Examples show that the proposed scheme outperforms the traditional layered scheme, both in terms of stable operating region as well as the end-to-end delays. We then propose a distributed routing scheme for a broad class of wireless sensor networks which converges (in the Cesaro sense) to the set of Cesaro-Wardrop equilibria. The scheme is based on multiple time-scale stochastic approximation algorithms. Convergence is established using standard results from the related literature and validated by simulation results. Our algorithm can adapt to changes in the network traffic and delays.
