Structure regularized traffic monitoring model for traffic matrix estimation and anomaly detection

doi:10.1109/ChiCC.2015.7260414

CORC > 北京大学 > 工学院

	Structure regularized traffic monitoring model for traffic matrix estimation and anomaly detection
	Zhang, Qi ; Chu, Tianguang
	2015
DOI	10.1109/ChiCC.2015.7260414
英文摘要	We consider the network traffic monitoring issue, including traffic matrix estimation and anomaly detection problems. New model called structure regularized traffic monitoring (SRTM) is presented by incorporating the spatial and temporal properties of the traffic matrices, with the sparsity of the traffic volume anomalies. The proposed SRTM model adapts more naturally to the engineering nature of the real traffic data and imposes structural regularizations. This stems from the fact that the real traffic data is usually approximately instead of exactly low-rank and exhibits strong spatial and temporal dependencies. In addition, we take advantages of the sparsity of the traffic volume anomalies and impose sparse constraints on the variables to detect the traffic anomalies. Efficient algorithm that based on the proximal gradient and gradient descent methods are proposed to solve the SRTM optimization model. Experiments in synthetic networks are carried out to verify the feasibility and effectiveness of the proposed model. ? 2015 Technical Committee on Control Theory, Chinese Association of Automation.; EI; 4980-4985; 2015-September
会议录	34th Chinese Control Conference, CCC 2015
语种	中文
内容类型	会议论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/423399]
专题	工学院
推荐引用方式 GB/T 7714	Zhang, Qi,Chu, Tianguang. Structure regularized traffic monitoring model for traffic matrix estimation and anomaly detection[C]. 见:.