A Computational Economy for IN Load Control Using A Multi-Agent System
A. Patel
Dept. of Electrical and Electronic Engineering
Imperial College of Science Technology and Medicine, London
Exhibition Road, London, UK, SW7 2BT
Email: a.patel1_AT_ic.ac.uk
K. Prouskas
Dept. of Electrical and Electronic Engineering
Imperial College of Science Technology and Medicine, London
Exhibition Road, London, UK, SW7 2BT
Email: k.prouskas_AT_ic.ac.uk
J. Barria
Dept. of Electrical and Electronic Engineering
Imperial College of Science Technology and Medicine, London
Exhibition Road, London, UK, SW7 2BT
Email: j.barria_AT_ic.ac.uk
J. Pitt
Dept. of Electrical and Electronic Engineering
Imperial College of Science Technology and Medicine, London
Exhibition Road, London, UK, SW7 2BT
Email: j.pitt_AT_ic.ac.uk
Abstract
Intelligent Networks (IN) are used in telecommunication networks to
provide services that require a decision-making network element. The Service
Control Point (SCP) can be overloaded when the number of service requests
exceeds the SCPs designed capacity. Traditional IN load control algorithms
assume a single service network model or use a centralized controller to
find a solution. In this paper we propose and investigate a market-based
model, in the form of a computational economy, for solving the distributed
IN load control problem for a multi-service network. We investigate two
algorithms, one price-oriented and the other resource-oriented, for finding
the competitive equilibrium for this economy. We conclude that the
price-oriented approach generally performs better and allows a greater level
of distributed-decision making but suffers from an infeasible solution in
real-time systems. Furthermore, we study a realization of this model as a
multi-agent system (MAS) and investigate the communication overhead
associated with running auctions for services.
Keywords: Intelligent Network, Congestion Control, Market-oriented Programming, Intelligent Agents
JNSM: Vol. 8, No. 3, 2000
A Computational Economy for IN Load Control Using A Multi-Agent System [Vol. 8, No. 3, 2000]
NOTE: only abstract of paper available on-line; please contact your library or the authors for the full paper
Back to JNSM main page