Data Mining for Managing Intrinsic Quality of Service in MPLS

Electronics and Electrical Engineering 2008
Jans Jeļinskis, Gunārs Lauks

LSP set up admission control policy is one of the notable problems that have to be solved to fulfill the requirements for effective resource allocation and network utilization for appropriate QoS level. In this paper, we verify a possibility of a new LSP setup admission algorithm, which uses optimization procedure based on multi-objective model with Pareto ranking and Genetic Algorithm. Decision rules are generated with Data Mining approach by performing classification operation to the selected data. This algorithm functions in two phases – classification and operating, which are accomplished consecutive. Algorithm is described and depicted. Experimental data are depicted and future research subjects are pointed. Ill. 4, bibl. 15

Keywords
Data Mining, MPLS, LSP set up, QoS
Hyperlink
http://eejournal.ktu.lt/index.php/elt/article/view/11156

Jeļinskis, J., Lauks, G. Data Mining for Managing Intrinsic Quality of Service in MPLS. Electronics and Electrical Engineering, 2008, Vol. 85, No. 5, pp.33-36. ISSN 1392-1215. e-ISSN 2029-5731.

Publication language
English (en)