北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2011, Vol. 34 ›› Issue (s1): 46-50.doi: 10.13190/jbupt.2011s1.46.guoshy

• 论文 • 上一篇    下一篇

基于用户行为聚类的移动终端业务故障检测优化机制

郭少勇,芮兰兰,邱雪松,孟洛明   

  1. 北京邮电大学 网络与交换国家重点实验室, 北京 100876
  • 出版日期:2011-10-28 发布日期:2011-10-28
  • 作者简介:郭少勇(1985-),男,博士生,E-mail:tcxgsy@yahoo.com.cn 孟洛明(1955-),男,教授,博士生导师
  • 基金资助:

    国家重点基础研究发展计划项目子课题(2007CB310703);国家自然科学基金国家创新研究群体科学基金项目(60821001);国家自然科学基金项目(60973108);国家科技重大专项项目 (2011ZX0300500402);中央高校基本科研业务费专项资金项目 (BUPT2009RC0504)

An Optimized UserBehavior Clustering Analysis Based Service  Fault Detection Mechanism for Mobile Device

    

  1.  
  • Online:2011-10-28 Published:2011-10-28
  • Supported by:
     

摘要:

为了检测、诊断以及排除移动终端上潜在的业务故障,提出面向用户的预检测机制以保障终端用户的正常使用. 首先引入用户终端的业务隶属度来反映用户的偏好,进而有差异性地对业务进行检测; 其次,根据业务隶属度情况,提出基于用户行为聚类模型,实现对用户的划分; 再次,综合业务隶属度、网络状态和业务历史故障率3个因素建立优先业务诊断集合的选取模型,既要保障将业务集合控制在用户最常用的范围内,又要保障对故障率较高的业务进行优先检测策略,进而达到以最小的代价最大可能地保障终端用户的正常使用; 最后,在移动终端故障管理原型系统中进行了验证.

关键词: 网络管理, 移动终端管理, 业务隶属度, 用户行为

Abstract:

In order to detect, diagnose and exclude potential or occurred faults on mobile devices, a useroriented detection mechanism is proposed. In the mechanism. A new UserBehavior Analysis model based on fuzzy math theory is firstly proposed to weigh the dependence degree of each service. Secondly, a UserBehavior Clustering Analysis model is introduced to divide mobile users into several clusters. Thirdly, integrations are made for the dependence degree of each service, the network status and failure rate of service into building a priority detectionservice set selection model. So the optimized sets for PreDetection of the service faults on mobile devices could be selected. Meanwhile, a UserBehavior Clustering Analysis Based Service Fault Detection Optimization Mechanism is implemented on a prototype system, and the optimal number of userclusters is validated judging by the average normal use ratio under three PreDetection scenarios.

Key words: network management, mobile device management, dependence degree, userbehavior

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