通信学报 ›› 2015, Vol. 36 ›› Issue (Z1): 110-117.doi: 10.11959/j.issn.1000-436x.2015288

• 学术论文 • 上一篇    下一篇

基于场景的移动应用服务QoS建模与评估

胡焰智1,2,章锋斌1,2,甘志春1,田田2,尹才华2   

  1. 1 国防信息学院 二系,湖北 武汉 430010
    2 重庆通信学院 二系,重庆 400035
  • 出版日期:2015-11-25 发布日期:2015-12-29
  • 基金资助:
    国家科技重大专项子课题基金资助项目

QoS modeling and evaluation of mobile application service based on scene

Yan-zhi HU1,2,Feng-bin ZHANG1,2,Zhi-chun GAN1,Tian TIAN2,Cai-hua YIN2   

  1. 1 The Second Deportment,National Defense Information Academy,Wuhan 430010,China
    2 The Second Deportment,Chongqing Communication College,Chongqing 400035,China
  • Online:2015-11-25 Published:2015-12-29
  • Supported by:
    The Sub-Topic of National Science and Technology Major Project

摘要:

针对目前静态服务QoS建模难以有效表征移动应用服务QoS的时变性和位置相关性,构建基于场景的移动应用服务QoS模型。定义移动应用服务QoS指标体系并构建了QoS数值对矩阵,提出服务QoS总体评估、特定区域或特定时段评估、热点区域或繁忙时段评估3类评估问题。采用遗传算法和数据聚类算法,通过服务请求位置密度实现区域自动划分,通过服务请求频次实现时段自动划分,量化位置区域和时间这2个场景条件,根据限定条件重构QoS数值对矩阵,基于QoS数值对矩阵的统计分析给出了服务QoS评估方法。最后阐述QoS归一化评估和应用框架。

关键词: 移动应用, 服务质量, 时变性, 位置相关

Abstract:

The current static QoS model can not reflect the QoS time varying and location correlation of mobile application service.An QoS model was presented based on scene for mobile applications service.The QoS index system of mobile application service was defined and the QoS value matrix was constructed.Further,three types of assessment problems were proposed,which were QoS overall assessment,QoS assessment of specific region or specific time periods,and QoS assessment of hot region and busy time.By using genetic algorithm and data clustering algorithm,the location and time of the two scene conditions were quantified,which combine the region division of service request location density and the time division of service request frequency.According to the limiting conditions,QoS value matrix was reconstructed,and the service evaluation method was introduced based on the statistical analysis of the matrix.Finally,the normalized evaluation process and application framework of QoS were given.

Key words: mobile application, service quality, time varying, location correlation

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