Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (4): 312-320.doi: 10.11896/jsjkx.210800027

• Computer Network • Previous Articles     Next Articles

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

PENG Dong-yang, WANG Rui, HU Gu-yu, ZU Jia-chen, WANG Tian-feng   

  1. Army Engineering University of PLA, Nanjing 210000, China
  • Received:2021-08-03 Revised:2021-12-08 Published:2022-04-01
  • About author:PENG Dong-yang,born in 1996,postgraduate.His main research interests include integrated application of big data and network management.HU Gu-yu,born in 1963,Ph.D,professor.His main research interests include network management and network intelligence.
  • Supported by:
    This work was supported by the National Natural Science Foundation of China(62076251).

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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

CLC Number: 

  • TP393
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