Paper Info
Title
Scalable URL matching with small memory footprint
Abstract
URL matching lies at the core of many networking applications and Information Centric Networking architectures. For example, URL matching is extensively used by Layer 7 switches, ICN/NDN routers, load balancers, and security devices. Modern URL matching is done by maintaining a rich database that consists of tens of millions of URL which are classified to dozens of categories (or egress ports). In real-time, any input URL has to be searched in this database to find the corresponding category. In this paper, we introduce a generic framework for accurate URL matching (namely, no false positives or miscategorization) that aims to reduce the overall memory footprint, while still having low matching latency. We introduce a dictionary-based compression method that compresses the database by 60%, while having only a slight overhead in time. Our framework is very flexible and it allows hot-updates, cloud-based deployments, and can deal with strings that are not URLs.
Year
DOI
Venue
2016
10.1109/IFIPNetworking.2016.7497218
2016 IFIP Networking Conference (IFIP Networking) and Workshops
Keywords
DocType
Citations 
cloud-based deployments,dictionary-based compression method,matching latency,security devices,load balancers,ICN/NDN routers,layer 7 switches,information centric networking architectures,networking applications,small memory footprint,scalable URL matching
Conference
0
PageRank 
References 
Authors
0.34
22
4
Name
Order
Citations
PageRank
Anat Bremler-Barr150539.95
David Hay218512.25
Daniel Krauthgamer300.34
Shimrit Tzur-David4132.62