Bloom-Quotient Based Name Matching Technique in Content Centric Networks

Abstract

Content Centric Networking (CCN) is a novel network paradigm in which the communication process focusses on content rather than the host. In the current network architecture, routers forward the incoming packets based on the routing information that already had. Whereas, forwarding decisions in CCN are taken depending on networks situation. The contents in CCN are retrieved depending on their names which are URL like names that are composing of a number of string parts separated by’/’. These names are stored inside a specific data structure, called Forwarding Information Base (FIB), inside CCN routers and they are used to forward any incoming packet. Therefore, the main two challenges that face the design of FIB table are: search speed and storage utilization. Consequently, in this paper, we propose a new name matching technique (named BF-QF FIB) to design and implement a FIB table in CCN routers in order to decrease the storage utilization and to increase the lookup speed. This technique utilizes two kinds of query data structures: Bloom filter (BF) and Quotient filter (QF) as its main data structures. The utilization of these two data structures will ensure low memory usage and high lookup speed. The results of our evaluation show that BF-QF FIB can guarantee high search rate and offer perfect scalability to large FIB tables.