Intelligent Deflection Routing in Buffer-Less Networks

被引:17
|
作者
Haeri, Soroush [1 ]
Trajkovic, Ljiljana [1 ]
机构
[1] Simon Fraser Univ, Sch Engn Sci, Burnaby, BC V5A 1S6, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Associative learning; buffer-less networks; decision-making; deflection routing; reinforcement learning; PERFORMANCE EVALUATION; OBS; ALGORITHMS; SELECTION; BOUNDS;
D O I
10.1109/TCYB.2014.2360680
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:316 / 327
页数:12
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