MULTISTEP AHEAD PREDICTION FOR REAL-TIME VBR VIDEO TRAFFIC USING DETERMINISTIC ECHO STATE NETWORK

摘要：

　　Variable bit rate (VBR) video traffic,exhibiting high self-similarity and burstiness,has been a major traffic component in high speed network.However,its complex bit rate distribution makes VBR video traffic prediction,especially multistep ahead prediction,very difficult.Recently,deterministic echo state network with adjacent-feedback loop reservoir structure (ALR) was proved to have high prediction accuracy,good memory capacity,and simple structure.In the paper,we apply ALR to real-time VBR video traffic prediction.The proposed scheme makes use of loop reservoir with identity activation function to conduct sample learning in high dimension states.Experimental results show that the simplified ALR scheme can effectively capture dynamic characteristics of VBR video traffic with less training time.Its multistep prediction accuracy is improved by 2% on average,compared with the neural network based on multi-resolution learning.

关键词： Echo state network Loop reservoir VBR video traffic Self-similarity Burstiness

作者: Xiaochuan Sun Hongyan Cui Renping Liu Jianya Chen Yunjie Liu

作者单位: Key Laboratory of Network System Architecture and Convergence,Beijing University of Posts and Teleco Key Laboratory of Network System Architecture and Convergence,Beijing University of Posts and Teleco ICT Centre,Commonwealth Scientific and Industrial Research Organization(CSIRO),Sydney 1710,Australia

会议类型: 国际会议

会议名称: 2012 2nd IEEE International Conference on Cloud Computing and Intelligence Systems (2012年第2届IEEE云计算与智能系统国际会议(IEEE CCIS2012))

会议地点: 杭州

会议语种:英文

页码: 1312-1315

在线出版日期: 2012-10-30（万方平台首次上网日期，不代表论文的发表时间）