Topological analysis of AOCD-based agent networks and experimental results
Topological analysis of intelligent agent networks provides crucial information about the structure of agent distribution over a network. Performance analysis of agent network topologies helps multi-agent system developers to understand the impact of topology on system efficiency and effectiveness. Appropriate topology analysis enables the adoption of suitable frameworks for specific multi-agent systems. In this paper, we systematically classify agent network topologies and propose a novel hybrid topology for distributed multi-agent systems. We compare the performance of this topology with two other common agent network topologies-centralised and decentralised topologies-within a new multi-agent framework, called Agent-based Open Connectivity for DSS (AOCD). Three major aspects are studied for estimating topology performance, which include (i) transmission time for a set of requests; (ii) waiting time for processing requests; and (iii),memory consumption for storing agent information. We also conduct a set of AOCD topological experiments to compare the performance of hybrid and centralised agent network topologies and illustrate our experimental results in this paper. (c) 2007 Elsevier Inc. All rights reserved.
aocd intelligent agents agent network topology agent network performance