This work presents an optimization-based methodology for integrating communication and controller design for uncertain process systems controlled over resource-constrained sensor-controller communication networks. The proposed methodology aims to enforce the desired closed-loop stability requirements while simultaneously optimizing the control system performance and network resource utilization. Initially, an auxiliary model-based networked controller is designed, and the relationship between the controller gain and the maximum allowable model-update period that ensures closed-loop stability under periodic sensor-controller communication is characterized. Based on this characterization, a finite-horizon optimization problem in which the cost function imposes explicit penalties on the model state, the control action and the model update frequency is formulated subject to appropriate closed-loop stability constraints. The optimization problem is solved in a receding horizon fashion to determine the optimal controller gain and optimal model update period needed at each update time. The receding horizon strategy results in time-varying gain and communication scheduling policies that allow the process to adapt more effectively to environmental uncertainties and perturbations. The implementation and efficacy of the developed optimization-based networked control approach are illustrated using a simulation example.