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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/407639 |
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| 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 |
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