From the microscopic and quantitative viewpoints,the connotation of the structural flexibility of reconfigurable networks was explored.More accurately,a key feature,i.e.,the dynamic data channel varying with service demands,of reconfigurable networks was first exhibited and explained.Four dominant implications of the flexibility were then revealed as gradually mapping to demands,keeping global performance good,implicit isolation,and self-driven control.Finally,related quantitative models and methods for both determining the stable deviation of outcomes from demands and computing the volume of resource dynamically reconfigured were investigated by using the exponentially moving average,the n:m voting scheme,Markov decision processes (MDP) and reinforcement learning,respectively.