[1]万明刚,李泽平,张军. 混合流媒体分发系统中多指标用户群分组算法[J].计算机技术与发展,2016,26(10):36-40.
　WAN Ming-gang,LI Ze-ping,ZHANG Jun. A User-group Grouping Algorithm Based on Multiple Indicators in Hybrid Streaming System[J].,2016,26(10):36-40.
点击复制

 混合流媒体分发系统中多指标用户群分组算法()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年10期
页码:
36-40
栏目:
智能、算法、系统工程
出版日期:
2016-10-10

文章信息/Info

Title:
 A  User-group Grouping Algorithm Based on Multiple Indicators in Hybrid Streaming System
文章编号:
1673-629X（2016)10-0036-05
作者:
 万明刚; 李泽平; 张军
 贵州大学 计算机科学与技术学院
Author(s):
 WAN Ming-gang; LI Ze-ping; ZHANG Jun
关键词:
 ; 混合流媒体分发系统; 节点位置; 网络类型; 节点兴趣; 分组; 服务节点选择
Keywords:
 ; hybrid streaming system; node location; Internet type; node interest; grouping; server node selection
分类号:
TP301.6
文献标志码:
A
摘要:
 针对混合流媒体分发系统中服务节点提供服务时出现额外的跨地域、跨网络开销以及搜索服务节点效率低下的问题，提出一种基于多指标的用户群分组算法，并应用于服务节点选择。依次分别利用节点位置和网络类型对用户群进行分组，将候选服务节点限制在同地域、同ISP范围内，以减少不必要的跨地域、跨网络开销；然后结合节点兴趣对用户群作进一步划分，将搜索服务节点的范围限制在兴趣组内，以减小搜索流量、提高搜索效率。仿真实验表明：提出的算法能有效将用户群分组，提高分发系统服务效率。
Abstract:
 To address the problem of additional cross-regional and cross-network cost that appears when the service node provides streaming media services,and the problem of inefficiency in searching service node,a grouping algorithm based on multiple indicators is proposed and used in server selection. As the algorithm goes,the user-group would be grouped by the node location and network type successively,limited the candidate server nodes in the same area and the same ISP,consequently reduced additional cross-regional and cross-network cost. Then the user-group would be divided further based on nodes’ interest,limited the search scope within an interest group,consequently reduced searching traffic and improved searching efficiency. Simulation demonstrates that the proposed algorithm can effectively divide the user-group,improving service efficiency.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
　ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(10):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
　LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(10):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
　HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(10):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
　HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(10):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
　LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(10):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
　WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(10):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
　LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(10):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
　SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(10):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
　YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(10):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
　YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(10):47.

更新日期/Last Update: 2016-11-25