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Deflection Routing in Complex Networks

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Part of the book series: Understanding Complex Systems ((UCS))

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Abstract

Deflection routing is a viable contention resolution scheme in buffer-less network architectures where contention is the main source of information loss. In recent years, various reinforcement learning-based deflection routing algorithms have been proposed. However, performance of these algorithms has not been evaluated in larger networks that resemble the autonomous system-level view of the Internet. In this Chapter, we compare performance of three reinforcement learning-based deflection routing algorithms by using the National Science Foundation network topology and topologies generated using Waxman and Barabási-Albert algorithms. We examine the scalability of these deflection routing algorithms by increasing the network size while keeping the network load constant.

Sections of this chapter appeared in conference proceedings and a journal publication: [27–30].

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Authors and Affiliations

  1. School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, BC V5A 1S6, Canada

    Soroush Haeri & Ljiljana Trajkovic

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  1. Soroush Haeri
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  2. Ljiljana Trajkovic
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Correspondence to Ljiljana Trajkovic .

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Editors and Affiliations

  1. Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China

    Jinhu Lü

  2. School of Electrical and Computer Engineering, RMIT University, Melbourne, Australia

    Xinghuo Yu

  3. Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China

    Guanrong Chen

  4. Department of Mathematics, Southeast University, Nanjing, China

    Wenwu Yu

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Haeri, S., Trajkovic, L. (2016). Deflection Routing in Complex Networks. In: Lü, J., Yu, X., Chen, G., Yu, W. (eds) Complex Systems and Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47824-0_15

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