Combinatorial clock auction for live video streaming in mobile edge computing

The live video streaming services have been suffered from the limited backhaul capacity of the cellular core network and occasional congestion on the Internet due to the cloud-based architecture. Mobile Edge Computing (MEC) brings the services from the centralized cloud to nearby base stations or edge devices to improve the Quality of Experience (QoE) of cloud services, such as live video streaming services. With the combination of Scalable Video Coding (SVC), MEC can significantly improve the QoE of live video streaming services. However, the resource at edge devices is still limited and should be allocated economically efficiently. In this paper, we propose the use of Combinatorial Clock Auction (CCA) in Streaming (CCAS), an auction framework to improve the QoE of live video streaming services in Edge-enabled cellular system. The edge system is the auctioneer who decides the caching space allocation and streamers are the bidders who request for the caching space to improve the video quality their audiences can watch. Two key subproblems are identified and can be solved by the proposed dynamic programming algorithms in the CCAS framework: the caching space value evaluations and allocations. We prove that the truth-telling property maintains and the time complexity of proposed algorithms runs in polynomial time to the number of streamers. The simulation results show that the overall system utility can be highly improved by the proposed framework.