CARE: Content Aware Redundancy Elimination for Challenged Networks
Abstract
This paper presents the design of a novel architecture called
CARE (Content-Aware Redundancy Elimination) that enables
maximizing the informational value that challenged
networks offer their users. We focus on emerging applications
for situational awareness in disaster affected regions.
Motivated by advances in computer vision algorithms, we
propose to incorporate image similarity detection algorithms
in the forwarding path of these networks. The purpose is to
handle the large generation of redundant content. We outline
the many issues involved in such a vision. With a DelayTolerant
Network (DTN) setup, our simulations demonstrate
that CARE can substantially boost the number of unique
messages that escape the disaster zone, and it can also deliver
them faster. These benefits are achieved despite the
energy overhead needed by the similarity detectors.