Controllable Multicast for Adaptive Scalable Video Streaming in Software-Defined Networks

Scalable video coding is a promising technique to enable flexible video transmission for heterogeneous terminals and varying channel throughput. However, it is challenging to perform in-network adaptation in conventional networks because the network nodes are uncontrollable and transparent for media streaming applications. Software-defined networking (SDN) is an attractive network technology that supports the applications to collaborate with network nodes to achieve intelligent and dynamic service provisioning. Against this changing network landscape, we redesign the scalable multimedia multicast streaming by exploiting the complete network knowledge of the SDN controller to enable intelligent scalable video transmission. The proposed scalable multimedia multicast streaming framework is capable of in-network identifying, processing, and manipulating the media streams. In order to achieve the in-network adaptation, we apply equivalent bandwidth theory to estimate the affordable video layers that a link may accommodate, and apply finite-state machine to implement adaptive enhancement layer switching for multicast paths. In contrast to IP multicast, the proposed method is a controllable multicast scheme, which provides admission control in a multicast context, in-network adaptation, and supporting heterogeneous devices having different display capability. We further implement a prototype for illustrating the success of the proposed solution. The experimental results are also presented to show the effectiveness of the proposed equivalent bandwidth based adaptive enhancement layer switching algorithm.