Fair Joint Optimization of QoE and Energy Efficiency in Caching Strategy for Videos

Abstract

With the increase in video traffic on wireless networks, content delivery networks and mobile edge computing are considered effective solutions to this problem, whereas caching strategy problem is an important issue of research.When facing different application scenarios and requirements, caching strategies are designed with different objectives.This study focuses on the fairness problem among different optimization objectives.For video service providers, the quality of experience (QoE) reflects the service performance, and energy efficiency reflects the cost-effectiveness and green energy-saving indicators.When designing a caching strategy, it is difficult to specify the objective with higher priority.Therefore, they need to be fairly optimized.First, the two important optimization objectives in the caching strategy problem(QoE and energy efficiency) are mathematically modeled, and the principle of fairness is proposed.Second, these two optimization objectives are innovatively consider as game players and are substituted into the Nash bargaining game model.Third, a multi-round bargaining algorithm is novelly proposed to ensure fairness, and the rationality and effectiveness of the proposed algorithm are rigorously proved.Finally, simulation experiments demonstrate that the proposed algorithm can optimize the QoE and energy efficiency of caching strategies while maintaining a ba-lance between them.

Keywords

• mec|video streaming|caching strategy|multi-objective optimization|fairness|nash bargaining game