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Resource allocation in communication networks using market-based agents

Resource allocation in communication networks using market-based agents
Resource allocation in communication networks using market-based agents
This work describes a system that allocates end-to-end bandwidth, in a switched meshed communications network. The solution makes use of market-based software agents that compete in a number of decentralised marketplaces to buy and sell bandwidth resources. Agents perform a distributed depth first search with decentralised markets in order to allocate routes for calls. The approach relies on a resource reservation and commit mechanism in the network. Initial results show that under a light network load, the system sets up a high percentage of calls which is comparable to the optimum value and that, under all network loads, it performs significantly better than a random strategy.
163-170
Haque, N.
54e3233b-7c32-4089-9432-90928401abdc
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Moreau, L.
033c63dd-3fe9-4040-849f-dfccbe0406f8
Haque, N.
54e3233b-7c32-4089-9432-90928401abdc
Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Moreau, L.
033c63dd-3fe9-4040-849f-dfccbe0406f8

Haque, N., Jennings, N. R. and Moreau, L. (2005) Resource allocation in communication networks using market-based agents. International Journal of Knowledge Based Systems, 18 (4-5), 163-170.

Record type: Article

Abstract

This work describes a system that allocates end-to-end bandwidth, in a switched meshed communications network. The solution makes use of market-based software agents that compete in a number of decentralised marketplaces to buy and sell bandwidth resources. Agents perform a distributed depth first search with decentralised markets in order to allocate routes for calls. The approach relies on a resource reservation and commit mechanism in the network. Initial results show that under a light network load, the system sets up a high percentage of calls which is comparable to the optimum value and that, under all network loads, it performs significantly better than a random strategy.

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More information

Published date: August 2005
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 261091
URI: https://eprints.soton.ac.uk/id/eprint/261091
PURE UUID: a816dda3-c8d3-43d1-af30-eb4605b28b22
ORCID for L. Moreau: ORCID iD orcid.org/0000-0002-3494-120X

Catalogue record

Date deposited: 10 Aug 2005
Last modified: 06 Jun 2018 13:03

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Contributors

Author: N. Haque
Author: N. R. Jennings
Author: L. Moreau ORCID iD

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