Since the pioneering work by Kelly et al. (1998) and Low-Lapsley (1999), there has been a concerted attempt to make congestion control a science rather than an art, by giving it a solid mathematical basis. In wired networks, this approach has found success in developing efficient new schemes. We describe our attempt to bridge the larger gap between theory and practice in rate control protocols for wireless networks. At the core of our approach is a new receiver capacity model that associates capacities with nodes instead of links. I will show how we have applied this model to design and implement the first explicit and precise distributed rate-based congestion control protocol for wireless sensor networks Ñ the wireless rate control protocol (WRCP), which can operate in asynchronous networks with dynamic traffic conditions. We show through extensive results from experiments that WRCP offers substantial improvements over the state of the art in flow completion times as well as in end-to-end packet delays. I will also discuss how the receiver capacity model can be used to implement rate optimization using shadow-pricing and queue back-pressure approaches.