Reliable and Efficient Multimedia Service Optimization for Edge Computing-Based 5G Networks: Game Theoretic Approaches
Tengfei Cao, Changqiao Xu, Junping Du, Yawen Li, Han Xiao, Changhui Gong, Lujie Zhong, Dusit Niyato
Abstract
The edge computing-based 5G networks have the advantages in efficiently offloading the large-scale Internet traffic, which is considered to be a promising architecture to alleviate the conflict between transmission performance and quality of experience (QoE). However, due to the unreliability of service providers and the mutual interference between wireless channels in 5G networks, it is still difficult for existing solutions to provide satisfactory multimedia services for mobile users. In response to these crucial challenges, this paper proposes a reliable and efficient multimedia service optimization framework named “REMSO” hereby, including a two-stage joint optimization procedure. Specifically, a reliable video service mechanism is first constructed to help the mobile users distinguish the credible and economic service BSs. Afterwards, an efficient wireless resource allocation strategy is established to achieve low latency and energy efficient video service optimization. In particular, the Stackelberg and potential game models are leveraged to achieve these optimization objectives. Finally, extensive simulations corroborate that our REMSO framework can deliver prominent performance advantages in terms of the reliability and efficiency when comparing with the state-of-the-art solutions.