DocumentCode
2310517
Title
Is the Popular R*-tree Suited for Packet Classification?
Author
Maindorfer, Christine ; Ottmann, Thomas
Author_Institution
Inst. fur Inf. Albert-Ludwigs, Univ. Freiburg Georges-Kohler-Allee, Freiburg
fYear
2008
fDate
10-12 July 2008
Firstpage
168
Lastpage
176
Abstract
Packet classification enables network routers to provide advanced network services including network security, quality of service (QoS) routing, and multimedia communications. In order to classify a packet, network nodes must perform a search over a set of filters using multiple fields of the packet as the search key. Viewing the classification problem geometrically, classifying an arriving packet is equivalent to finding the highest priority hyperrectangle among all hyperrectangles that contain the point representing the packet. The R-tree and its variants, being among the most popular access methods for points and rectangles, have not been experimentally evaluated and benchmarked for their eligibility for the packet classification problem. In this paper we investigate how the R*-tree, a dynamic index structure for spatial data, is suited for packet classification. To this end we will benchmark R* with two representative classification algorithms using the ClassBench tools suite.
Keywords
IP networks; multimedia communication; quality of service; telecommunication network routing; telecommunication security; trees (mathematics); ClassBench tools; QoS; R*-tree; multimedia communications; network security; packet classification; quality of service routing; Classification algorithms; Communication system security; Computer applications; Computer networks; Data security; Hydrogen; Matched filters; Multimedia communication; Quality of service; Routing; Packet classification; Performance evaluation; R*-tree; Spatial access method;
fLanguage
English
Publisher
ieee
Conference_Titel
Network Computing and Applications, 2008. NCA '08. Seventh IEEE International Symposium on
Conference_Location
Cambridge, MA
Print_ISBN
978-0-7695-3192-2
Electronic_ISBN
978-0-7695-3192-2
Type
conf
DOI
10.1109/NCA.2008.20
Filename
4579653
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