Cache-Aware Joint Cell Association and Version Selection for Network Assisted DASH

In the mobile video era, dynamic adaptive streaming over HTTP (DASH) is widely concerned due to its favorable performance in time-variant channel environments. Although DASH follows a decentralised and client-pull paradigm, networks are expected to play a more active role to assist rate adaption. On the other hand, heterogeneous cellular networks (HetNet) are considered as an efficient solution to cope with the exponential growth of mobile traffic, where cell association is one of the key issues. However, most of existing association methods were not designed for DASH services. In this paper, we jointly consider both the selection of multiple video versions for network- assisted DASH and the association strategy for cache- enabled HetNet. We aim to guarantee a premium quality of experience (QoE) with DASH over HetNet. An integer optimization problem is formulated and simplified into a multiple-choice knapsack sub-problem and a many-to- one matching sub-problem. A joint cell association and version selection approach is proposed through problem solving. In our scheme, users are associated with small cells and select different versions according to the required rates of video versions, channel conditions, cache states and the traffic loads. Simulation results show the effectiveness of our proposed method.