With the advances in hand-held devices (smartphones and tablets, etc.) and high speed wireless networks, users have an explosive growth demand for live streaming service. Due to the diversity of user equipments (UEs), the live streaming has to be transcoded into different versions. However, transcoding is a computationally expensive and time consuming process. Due to the dynamic characteristics of wireless network environment, providing high quality and low latency live videos for UEs is a big challenge. This study investigates user scheduling, transcoding decision, computational and wireless spectrum resources allocation problem in edge-clouds aided heterogeneous networks (HetNets). The research focuses on improving UEs' quality of service (QoS) for live-streaming services, which includes quality of video and latency requirements. Different from existing literature, to approach the real wireless environment, the available computational and wireless spectrum resources are modeled as random processes in the work. Considering dynamic characteristics of wireless networks and available resources, the above problem is modeled as a Markov decision process (MDP). Since the action space of the MDP is multi-dimensional continuous variables mixed with discrete variables, it is difficult to solve this problem by traditional learning algorithms. Therefore, an enhanced actor-critic algorithm is proposed to resolve the problem, in which both the actor part and the critic part employ eligibility traces. Extensive simulation results with different system parameters show the effectiveness of the proposed algorithm.

Additional Metadata
Keywords actor-critic algorithm, edge computing, Live-streaming, quality of service, resource allocation
Persistent URL dx.doi.org/10.1109/TVT.2019.2942629
Journal IEEE Transactions on Vehicular Technology
Citation
Zhang, Z. (Zhicai), Wang, R. (Ru), Yu, F.R, Fu, F. (Fang), & Yan, Q. (Qiao). (2019). QoS Aware Transcoding for Live Streaming in Edge-Clouds Aided HetNets: An Enhanced Actor-Critic Approach. IEEE Transactions on Vehicular Technology, 68(11), 11295–11308. doi:10.1109/TVT.2019.2942629