Thanks to recent advances in hierarchical video coding and overlay network, layered overlay multicast has emerged as an important solution for video streaming over heterogeneous network. In this paper, we formulate it into a joint network flow control and performance optimization problem where adaptive layer rates are determined through a greedy algorithm close to optimal. The overlay network is constrained by a practical two-level hierarchical overlay model where the bandwidth sharing is imposed on underlying edge-bottleneck links. To maintain less computational complexity and avoidance of global information, the $M$-layer maximization problem is transformed into multiple one-layer minimization subproblems. In turn, a fully distributed algorithm is developed by decomposing the one-layer minimization problem into both inequality constrained transportation subproblem and the shortest path subproblem by using Lagrangian duality. We demonstrate that the distributed algorithm converges quickly and attains effective performance in both static and dynamic networks.