A central issue in two-sided matching markets such as Cloud-Based Design and Manufacturing (CBDM) where agents interact over a long period of time is the design of optimal matching period during recursive implementation. Existing literature provides mechanisms that satisfy useful properties such as stability in a single matching cycle, but they lack studies on the effect of the period of matching cycle on the optimality. To address this gap, we perform simulation studies on a synthetic CBDM scenario where service seekers arrive as a Poisson process with a fixed number of service providers offering resources. We identify the optimal matching period and assess its robustness using sensitivity studies. Optimality is measured in terms of utility obtained by the agents, the number of matches and fairness of the utility distribution. We show that a matching period equal to the ratio of the number of service providers to the arrival rate of service seekers is optimal.