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Joint congestion control and scheduling has been widely applied to resource allocation in multi-hop wireless networks. Existing algorithms usually rely on seamless cooperation between network components to seek the optimal solution. However, this is unrealistic considering the presence of time delay and channel capacity perturbation in real wireless environments. The stability and efficiency of these cross-layer control algorithms face significant challenges. In this paper we present ROCS: a robust joint congestion control and scheduling algorithm for time-varying multihop wireless networks with time delay, to bridge the gap between the existing results and the reality of wireless networks. The fundamental idea behind ROCS is Capacity Space Mapping, which combines the slow time scale part of the original channel capacity and a margin estimated from the fast time scale part, to form a new capacity space. The cross-layer resource allocation problem is formulated into a utility maximization framework over the newly generated capacity space. The problem is solved by a control algorithm which contains two closely coupled components: Link Scheduling and Congestion Control. Link Scheduling coordinates wireless link utilization on a maximum weight basis, and Congestion Control allocates flow rates according to congestion feedback information. We further derive the sufficient conditions for the Lyapunov stability of the control algorithm with time delay, following the Razumikhin theorem. We demonstrate via extensive experiments conducted over simulated and real world wireless traces that ROCS substantially achieves robustness and efficiency.