Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems

Building efficient distributed coordination algorithms is critical for the large scale multiagent system design, and the communication network has been shown as a key factor to influence system performance even under the same coordination protocol. Although many distributed algorithm designs have be...

Full description

Saved in:
Bibliographic Details
Main Authors: Yang Xu, Pengfei Liu, Xiang Li, Wei Ren
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/407639
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849407345337040896
author Yang Xu
Pengfei Liu
Xiang Li
Wei Ren
author_facet Yang Xu
Pengfei Liu
Xiang Li
Wei Ren
author_sort Yang Xu
collection DOAJ
description Building efficient distributed coordination algorithms is critical for the large scale multiagent system design, and the communication network has been shown as a key factor to influence system performance even under the same coordination protocol. Although many distributed algorithm designs have been proved to be feasible to build their functions in the large scale multiagent systems as claimed, the performances may not be stable if the multiagent networks were organized with different complex network topologies. For example, if the network was recovered from the broken links or disfunction nodes, the network topology might have been shifted. Therefore, their influences on the overall multiagent system performance are unknown. In this paper, we have made an initial effort to find how a standard network recovery policy, MPLS algorithm, may change the network topology of the multiagent system in terms of network congestion. We have established that when the multiagent system is organized as different network topologies according to different complex network attributes, the network shifts in different ways. Those interesting discoveries are helpful to predict how complex network attributes influence on system performance and in turn are useful for new algorithm designs that make a good use of those attributes.
format Article
id doaj-art-4414661bffaf482eae4d65c004d4a0d4
institution Kabale University
issn 2356-6140
1537-744X
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-4414661bffaf482eae4d65c004d4a0d42025-08-20T03:36:06ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/407639407639Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent SystemsYang Xu0Pengfei Liu1Xiang Li2Wei Ren3School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaSchool of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, ChinaBuilding efficient distributed coordination algorithms is critical for the large scale multiagent system design, and the communication network has been shown as a key factor to influence system performance even under the same coordination protocol. Although many distributed algorithm designs have been proved to be feasible to build their functions in the large scale multiagent systems as claimed, the performances may not be stable if the multiagent networks were organized with different complex network topologies. For example, if the network was recovered from the broken links or disfunction nodes, the network topology might have been shifted. Therefore, their influences on the overall multiagent system performance are unknown. In this paper, we have made an initial effort to find how a standard network recovery policy, MPLS algorithm, may change the network topology of the multiagent system in terms of network congestion. We have established that when the multiagent system is organized as different network topologies according to different complex network attributes, the network shifts in different ways. Those interesting discoveries are helpful to predict how complex network attributes influence on system performance and in turn are useful for new algorithm designs that make a good use of those attributes.http://dx.doi.org/10.1155/2014/407639
spellingShingle Yang Xu
Pengfei Liu
Xiang Li
Wei Ren
Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
The Scientific World Journal
title Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
title_full Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
title_fullStr Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
title_full_unstemmed Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
title_short Discovering the Influences of Complex Network Effects on Recovering Large Scale Multiagent Systems
title_sort discovering the influences of complex network effects on recovering large scale multiagent systems
url http://dx.doi.org/10.1155/2014/407639
work_keys_str_mv AT yangxu discoveringtheinfluencesofcomplexnetworkeffectsonrecoveringlargescalemultiagentsystems
AT pengfeiliu discoveringtheinfluencesofcomplexnetworkeffectsonrecoveringlargescalemultiagentsystems
AT xiangli discoveringtheinfluencesofcomplexnetworkeffectsonrecoveringlargescalemultiagentsystems
AT weiren discoveringtheinfluencesofcomplexnetworkeffectsonrecoveringlargescalemultiagentsystems