An Adaptive Hierarchical Hybrid Multicast Based on Information-Centric Networking

Many information-centric services have emerged, such as IPTV and video conferencing. These services put a lot of demands on scalable multicast communication. However, traditional IP multicast has low adoption because of its poor scalability. Therefore, some stateless multicast methods were proposed, which encapsulate the destination’s information into the packet header without requiring routers to maintain the multicast forwarding state. However, stateless multicast also faces some problems, such as ingress router overload, high forwarding overhead, packet redundancy, etc. In addition, most multicast methods cannot optimize the multicast tree because the multicast flow is simply forwarded along the shortest path tree from the source to receivers. This paper proposes an Adaptive Hierarchical Hybrid Multicast (AHHM) based on Information-Centric Networking. To balance the forwarding states and forwarding overhead, AHHM is designed as a two-layer structure, in which the upper layer establishes a stateful main tree and the lower layer establishes several stateless sub trees. The router on the main tree is defined as the multicast join node (MJN), and AHHM uses the Name Resolution System to maintain the mapping between each multicast group name and corresponding MJNs. To optimize the multicast transmission path, we designed the minimum cost selection strategy for users to select the appropriate MJN to join. Simulation results show that compared with Source-Specific Multicast (SSM) and Bit Index Explicit Replication (BIER), AHHM can not only reduce the multicast forwarding states but also reduce the control overhead and link load.