Data Dissemination in Cognitive Radio Networks

TL;DR

This paper introduces SURF, a novel channel selection strategy for data dissemination in multi-hop cognitive radio networks, evaluated through simulations and compared with existing methods.

Contribution

The paper proposes SURF, a new channel selection approach tailored for cognitive radio networks, with evaluation in single-hop and multi-hop scenarios.

Findings

SURF outperforms existing strategies in certain network conditions.

Evaluation shows improved data dissemination efficiency.

The approach is adaptable to various network topologies.

Abstract

In this report, we first describe the problem that we are dealing with i.e. data dissemination in multi-hop cognitive radio networks. To address this problem, we propose a channel selection strategy named 'SURF'. We evaluate the proposed channel selection strategy in both single-hop and multi-hop scenarios and compared it with relevant approaches. So far, one technical report and a poster is published as part of this work, while two publications are under review; one is in IEEE Communications Letters and the second one is in IEEE WoWMoM conference. In on-going works sections, we first mention some possible directions in the context of SURF. In addition to that, we mention different research problems that we are planning to deal during the course of this PhD dissertation.