DocumentCode :
1884978
Title :
A Criterion for Speed Evaluation of Content Inspection Engines
Author :
Yazdani, Mohammadreza ; Fraczak, Wojciech ; Welfeld, Feliks ; Lambadaris, Ioannis
Author_Institution :
Carleton University, Ottawa, Canada
fYear :
2006
fDate :
23-29 April 2006
Firstpage :
19
Lastpage :
19
Abstract :
The growing needs of network security and contentaware networking increasingly introduce content processing into the network devices as opposed to the network endpoints. The component of a network device responsible for content inspection is called Content Inspection Engine (CIE). As other components of a network device, the CIE needs to operate at wire-speed, posing a need to look for an appropriate speed-evaluation criterion for CIEs. For processes with constant or at most well-bounded per-packet analyzes (e.g., routing, multi-field packet classification), and processes with flat per-byte processing time (e.g., checksum calculation, encryption/decryption), operation speed is traditionally evaluated in terms of the number of packets or bits processed per second. Such metrics cannot be used for processes in which the processing time of a packet varies widely, depending on its content. We propose to define worst-case throughput as a criterion for evaluating the wire-speed processing capabilities of CIEs. We argue that one may build simple model of a CIE, whether hardware or software based, in the form of a directed graph with edges annotated by the length and processing time of the segments of input data. It is then possible to transform the problem of finding the worst-case throughput of a CIE to the minimum cost to time ratio problem, for which many efficient algorithms exist.
Keywords :
Computer networks; Computer security; Costs; Engines; Inspection; Payloads; Routing; Systems engineering and theory; Telecommunication traffic; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies, 2006. ICN/ICONS/MCL 2006. International Conference on
Print_ISBN :
0-7695-2552-0
Type :
conf
DOI :
10.1109/ICNICONSMCL.2006.8
Filename :
1628265
Link To Document :
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