Enhancing Video Rate Adaptation with Mobile Edge Computing and Caching in Software-defined Mobile Networks
Recent advances in software-defined mobile networks (SDMNs), in-network caching, and mobile edge computing (MEC) can have significant effects on video services in next generation mobile networks. In this article, we jointly consider SDMNs, in-network caching, and MEC to enhance the video service in next generation mobile networks. We use a new video experience evaluation standard called U-vMOS, which is a more advanced measurement of the video quality based on the well-known video mean opinion score (vMOS).With the objective of maximizing the mean U-vMOS, an optimization problem is formulated. Due to the coupling of video data rate, computing resource, and traffic engineering (bandwidth provisioning and paths selection), the problem becomes intractable in practice. Thus, we utilize dualdecomposition method to decouple those three sets of variables. By this decoupling, video rate adaptation is performed at users with network assistants. End nodes can schedule computing resource independently. Traffic engineering is performed by the software-defined networking (SDN) controller and base stations (BSs). Furthermore, to address the challenges of dynamic change of network status and the drawbacks caused by the frequent exchange of information, we design a decentralized algorithm based on alternating direction method of multipliers to solve the traffic engineering problem. Extensive simulations are conducted with different system configurations to show the effectiveness of the proposed scheme.
|Keywords||in-network caching, mobile edge computing, Next generation networking, Quality assessment, Quality of experience, Servers, software-defined mobile networks, Streaming media, traffic engineering, Video rate adaptation, Video recording, Wireless communication|
|Journal||IEEE Transactions on Wireless Communications|
Liang, C. (Chengchao), He, Y. (Ying), Yu, F.R, & Zhao, N. (Nan). (2018). Enhancing Video Rate Adaptation with Mobile Edge Computing and Caching in Software-defined Mobile Networks. IEEE Transactions on Wireless Communications. doi:10.1109/TWC.2018.2865354