A Framework and Model for Soft Routing: The Markovian Termite and Other Curious Creatures

  • Martin Roth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)


A theoretical framework and model is presented to study the self-organized behavior of probabilistic routing protocols for computer networks. Such soft routing protocols have attracted attention for delivering packets reliably, robustly, and efficiently. The framework supports several features necessary for emergent routing behavior, including feedback loops and indirect communication between peers. Efficient global operating parameters can be estimated without resorting to expensive monte-carlo simulation of the whole system. Key model parameters are routing sensitivity and routing threshold, or noise, which control the “randomness” of packet routes between source and destination, and a metric estimator. Global network characteristics are estimated, including steady state routing probabilities, average path length, and path robustness.

The framework is based on a markov chain analysis. Individual network nodes are represented as states. Standard techniques are used to find primary statistics of the steady state global routing pattern, given a set of link costs. The use of packets to collect information about, or “sample,” the network for new path information is also reviewed. How the network sample rate influences performance is investigated.


Particle Swarm Optimization Path Cost Link Cost Link Utility Packet Arrival Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Martin Roth
    • 1
  1. 1.Deutsche Telekom LaboratoriesBerlinGermany

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