Consensus-based clustering and data aggregation in decentralized network of multi-agent systems
Multi-agent systems are promising for applications in various fields. However, they require optimization algorithms that can handle large number of agents and heterogeneously connected networks in clustered environments. Planning algorithms performed in the decentralized communication model and clus...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2023-08-01
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| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-1445.pdf |
| _version_ | 1797732204279758848 |
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| author | Joshua Julian Damanik Ming Chong Lim Hyeon-Mun Jeong Ho-Yeon Kim Han-Lim Choi |
| author_facet | Joshua Julian Damanik Ming Chong Lim Hyeon-Mun Jeong Ho-Yeon Kim Han-Lim Choi |
| author_sort | Joshua Julian Damanik |
| collection | DOAJ |
| description | Multi-agent systems are promising for applications in various fields. However, they require optimization algorithms that can handle large number of agents and heterogeneously connected networks in clustered environments. Planning algorithms performed in the decentralized communication model and clustered environment require precise knowledge about cluster information by compensating noise from other clusters. This article proposes a decentralized data aggregation algorithm using consensus method to perform COUNT and SUM aggregation in a clustered environment. The proposed algorithm introduces a trust value to perform accurate aggregation on cluster level. The correction parameter is used to adjust the accuracy of the solution and the computation time. The proposed algorithm is evaluated in simulations with large and sparse networks and small bandwidth. The results show that the proposed algorithm can achieve convergence on the aggregated data with reasonable accuracy and convergence time. In the future, the proposed tools will be useful for developing a robust decentralized task assignment algorithm in a heterogeneous multi-agent multi-task environment. |
| first_indexed | 2024-03-12T12:09:57Z |
| format | Article |
| id | doaj.art-b3f916b581834848b88209eef052818a |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-03-12T12:09:57Z |
| publishDate | 2023-08-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-b3f916b581834848b88209eef052818a2023-08-30T15:05:05ZengPeerJ Inc.PeerJ Computer Science2376-59922023-08-019e144510.7717/peerj-cs.1445Consensus-based clustering and data aggregation in decentralized network of multi-agent systemsJoshua Julian DamanikMing Chong LimHyeon-Mun JeongHo-Yeon KimHan-Lim ChoiMulti-agent systems are promising for applications in various fields. However, they require optimization algorithms that can handle large number of agents and heterogeneously connected networks in clustered environments. Planning algorithms performed in the decentralized communication model and clustered environment require precise knowledge about cluster information by compensating noise from other clusters. This article proposes a decentralized data aggregation algorithm using consensus method to perform COUNT and SUM aggregation in a clustered environment. The proposed algorithm introduces a trust value to perform accurate aggregation on cluster level. The correction parameter is used to adjust the accuracy of the solution and the computation time. The proposed algorithm is evaluated in simulations with large and sparse networks and small bandwidth. The results show that the proposed algorithm can achieve convergence on the aggregated data with reasonable accuracy and convergence time. In the future, the proposed tools will be useful for developing a robust decentralized task assignment algorithm in a heterogeneous multi-agent multi-task environment.https://peerj.com/articles/cs-1445.pdfSituational awarenessClusteringAggregationMulti-agent systemsOptimizationConsensus |
| spellingShingle | Joshua Julian Damanik Ming Chong Lim Hyeon-Mun Jeong Ho-Yeon Kim Han-Lim Choi Consensus-based clustering and data aggregation in decentralized network of multi-agent systems PeerJ Computer Science Situational awareness Clustering Aggregation Multi-agent systems Optimization Consensus |
| title | Consensus-based clustering and data aggregation in decentralized network of multi-agent systems |
| title_full | Consensus-based clustering and data aggregation in decentralized network of multi-agent systems |
| title_fullStr | Consensus-based clustering and data aggregation in decentralized network of multi-agent systems |
| title_full_unstemmed | Consensus-based clustering and data aggregation in decentralized network of multi-agent systems |
| title_short | Consensus-based clustering and data aggregation in decentralized network of multi-agent systems |
| title_sort | consensus based clustering and data aggregation in decentralized network of multi agent systems |
| topic | Situational awareness Clustering Aggregation Multi-agent systems Optimization Consensus |
| url | https://peerj.com/articles/cs-1445.pdf |
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