Title :
A Sparse Dirty Data Process Method Based on Alternative Projection for Traffic Matrix Estimation
Author :
Feng, Yu ; Zaiyue, Zhang ; Wei, Li ; Lalin, Jiang
Author_Institution :
Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., Zhenjiang, China
Abstract :
Estimation of traffic matrices, which provides critical input for network capacity planning and traffic engineering, will be contaminated by the dirty data created by troubles such us hardware/software/transmission. To solve this problem, a SNMP-data-self based sparse dirty data model and a sparse dirty data processing algorithm based on alternating projection are proposed here. The former occupies merit of no checkout between measurement of OD flows and SNMP data, the latter obtains norm minimized solution through alternating projection method. Comparing to other main algorithms, this method has lower measuring overhead and computing complexity. Moreover, the simulation experiment shows high accuracy.
Keywords :
Internet; computational complexity; protocols; telecommunication traffic; computational complexity; network capacity planning; simple network management protocol; sparse dirty data process method; traffic engineering; traffic matrix estimation; Capacity planning; Computational modeling; Data engineering; Data models; Data processing; Hardware; Pollution measurement; Sparse matrices; Telecommunication traffic; Traffic control; alternating projection; sparse dirty data; traffic matrix;
Conference_Titel :
Industrial and Information Systems, 2009. IIS '09. International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-3618-7
DOI :
10.1109/IIS.2009.68