To maximize the aggregate throughput achieved in heterogeneous networks, this paper investi- gates inter-session network coding for the distribution of layered source data. We define inter-layer hierarchical random linear network codes (IHRLNC), which not only take the flexibility of inter- session network coding for layer mixing but also consider the strict priority inherent in the layered source data. Furthermore, we propose the inter-layer hierarchical multicast (IHM), which performs IHRLNC in the network such that each sink can recover some source layers according to its individu- al capacity. To determine the optimal type of IHRLNC that should be performed on each edge in IHM, we formulate an optimization problem based on 0-1 integer linear programming, and propose a heuristic approach to approximate the optimal solution in polynomial time. Simulation results show that the proposed IHM can achieve throughput gains over the layered muhicast schemes.