Memory Efficient Forwarding Information Base for Content-Centric Networking

TL;DR

This paper explores memory-efficient data structures for the Forwarding Information Base in Content-Centric Networking, focusing on IoT devices with limited memory, and recommends Bloom-Filters or hashes based on specific scenarios.

Contribution

It analyzes requirements for FIBs in IoT, surveys solutions, and proposes optimized implementations using hashes and Bloom-Filters for memory efficiency.

Findings

Bloom-Filters are recommended for large prefix sets with uniform distribution.

Hash-based FIBs are preferable in other scenarios.

The study provides guidelines for FIB design in IoT environments.

Abstract

Content-Centric Networking (CCN) is a new paradigm for the future Internet where content is addressed by hierarchically organized names with the goal to replace TCP/IP networks. Unlike IP addresses, names have arbitrary length and are larger than the four bytes of IPv4 addresses. One important data structure in CCN is the Forwarding Information Base (FIB) where prefixes of names are stored together with the forwarding face. Long prefixes create problems for memory constrained Internet of Things (IoT) devices. In this work, we derive requirements for a FIB in the IoT and survey possible solutions. We investigate, design and compare memory-efficient solutions for the FIB based on hashes and Bloom-Filters. For large number of prefixes and an equal distribution of prefixes to faces we recommend a FIB implementation based on Bloom-Filters. In all other cases, we recommend an implementation of the FIB with hashes.