视频缓存策略中QoE和能量效率的公平联合优化

doi:10.11896/jsjkx.210800027

摘要/Abstract

摘要： 随着无线网络中视频流量的增长,内容分发网络和移动边缘计算技术被视为应对这一挑战的有效方案,其中缓存策略问题是研究的重要内容。面对不同的应用场景和需求,设计缓存策略时会考虑不同的优化目标。文中重点考虑了两个优化目标的公平性问题。对视频服务商而言,用户满意度(Quality of Experience,QoE)体现了服务的质量,而能量效率体现了成本效益和节能指标。在设计缓存策略时,由于无法明确哪个目标的优先级更高,因此需要对它们进行公平地优化。首先,对缓存策略问题的两个重要目标(QoE和能量效率)进行数学建模,并提出了公平性原则。然后,将这两个优化目标作为博弈对象,代入纳什议价博弈模型中。接着,提出了一种确保公平性的多回合议价算法,并证明了该算法的合理性和有效性。最后,仿真实验验证,该算法能够在优化缓存策略的QoE和能量效率的同时保证它们之间的公平性。

关键词: 多目标优化, 公平性, 缓存策略, 流媒体视频, 纳什议价博弈, 移动边缘计算

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.

Key words: Caching strategy, Fairness, MEC, Multi-objective optimization, Nash bargaining game, Video streaming

中图分类号:

TP393

彭冬阳, 王睿, 胡谷雨, 祖家琛, 王田丰. 视频缓存策略中QoE和能量效率的公平联合优化[J]. 计算机科学, 2022, 49(4): 312-320. https://doi.org/10.11896/jsjkx.210800027

PENG Dong-yang, WANG Rui, HU Gu-yu, ZU Jia-chen, WANG Tian-feng. Fair Joint Optimization of QoE and Energy Efficiency in Caching Strategy for Videos[J]. Computer Science, 2022, 49(4): 312-320. https://doi.org/10.11896/jsjkx.210800027

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