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Packet Classification Using Cross-Producting (pp.223-252) $100.00
Authors:  (Pi-Chung Wang, Department of Computer Science, National Chung Hsing University, Taichung, Taiwan, R.O.C.)
Abstract:
Packet classification has become one of the most important application techniques in
network security since the last decade. The technique involves a traffic descriptor or
user-defined criteria to categorize packets to a specific forwarding class which will be
accessible for future security handling.
In this chapter, we present two new schemes, Hierarchical Cross-Producting and
Controlled Cross-producting, to achieve fast packet classification. The first scheme
simplifies the classification procedure and decreases the distinct combinations of fields
by hierarchically decomposing the multi-dimensional space based on the concept of
telescopic search. Analogous to the use of telescopes with different powers, which
is defined as the degree to which a telescope multiplies the apparent diameter of an
object in optical terms, a multiple-step process is used to search for targets. In this
scheme, the multi-dimensional space is endowed with a hierarchical property which
self-divides into several smaller subspaces, whereas the procedure of packet classification
is translated into recursive searching formatching subspaces. The required storage
of our scheme could be significantly reduced since the distinct field specifications of
subspaces are manageable. Next, we combine the technique of cross-producting with
linear search to make packet classification both fast and scalable. The new algorithm,
ControlledCross-producting, could improve the scalability of cross-producting significantly
with respect to storage, while maintaining the search latency. In addition, we
introduce several refinements and procedures for incremental update.
The performance of both algorithms is evaluated based on both real and synthetic
filter databases. The experimental results demonstrate the effectiveness and scalability
of both schemes. 


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Packet Classification Using Cross-Producting (pp.223-252)