Adaptive Agent-Driven Routing and Load Balancing in Communication Networks
Martin Heusse,
Dominique Snyers (),
Sylvain Guérin and
Pascale Kuntz
Additional contact information
Martin Heusse: ENST de Bretagne, BP 832, Brest Cedex, France
Dominique Snyers: ENST de Bretagne, BP 832, Brest Cedex, France
Sylvain Guérin: ENST de Bretagne, BP 832, Brest Cedex, France
Pascale Kuntz: ENST de Bretagne, BP 832, Brest Cedex, France
Advances in Complex Systems (ACS), 1998, vol. 01, issue 02n03, 237-254
Abstract:
This paper presents an unified overview of a new family of distributed algortithms for routing and load balancing in dynamic communication networks. These new algorithms are described as an extension to the classical routing algorithms: they combine the ideas of online asynchronous distance vector routing with adaptive link state routing. Estimates of the current traffic condition and link costs are measured by sending routing agents in the network that mix with the regular information packets and keep track of the costs (e.g. delay) encountered during their journey. The routing tables are then regularly updated based on that information without any central control nor complete knowledge of the network topology. Two new algorithms are proposed here. The first one is based on round trip routing agents that update the routing tables by backtracking their way after having reached the destination. The second one relies on forward agents that update the routing tables directly as they move toward their destination. An efficient co-operative scheme is proposed to deal with asymmetric connections. All these methods are compared on a simulated network with various traffic loads; the robustness of the new algorithms to network changes is proved on various dynamic scenarii.
Keywords: Routing; load balancing; QoS; multi-agents; Q-learning; dynamic programming. (search for similar items in EconPapers)
Date: 1998
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:01:y:1998:i:02n03:n:s0219525998000168
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DOI: 10.1142/S0219525998000168
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