IEEE Trans Cybern. 2015 Feb;45(2):316-27. doi: 10.1109/TCYB.2014.2360680. Epub 2014 Dec 18.
IEEE transactions on cybernetics
Soroush Haeri, Ljiljana Trajković
PMID: 25532199 DOI: 10.1109/TCYB.2014.2360680
Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.
