Consensus formation on heterogeneous networks
Abstract Reaching consensus—a macroscopic state where the system constituents display the same microscopic state—is a necessity in multiple complex socio-technical and techno-economic systems: their correct functioning ultimately depends on it. In many distributed systems—of which blockchain-based a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-06-01
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| Series: | EPJ Data Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1140/epjds/s13688-022-00347-5 |
| _version_ | 1818234966199238656 |
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| author | Edoardo Fadda Junda He Claudio J. Tessone Paolo Barucca |
| author_facet | Edoardo Fadda Junda He Claudio J. Tessone Paolo Barucca |
| author_sort | Edoardo Fadda |
| collection | DOAJ |
| description | Abstract Reaching consensus—a macroscopic state where the system constituents display the same microscopic state—is a necessity in multiple complex socio-technical and techno-economic systems: their correct functioning ultimately depends on it. In many distributed systems—of which blockchain-based applications are a paradigmatic example—the process of consensus formation is crucial not only for the emergence of a leading majority but for the very functioning of the system. We build a minimalistic network model of consensus formation on blockchain systems for quantifying how central nodes—with respect to their average distance to others—can leverage on their position to obtain competitive advantage in the consensus process. We show that in a wide range of network topologies, the probability of forming a majority can significantly increase depending on the centrality of nodes that initiate the spreading. Further, we study the role that network topology plays on the consensus process: we show that central nodes in scale-free networks can win consensus in the network even if they broadcast states significantly later than peripheral ones. |
| first_indexed | 2024-12-12T11:46:28Z |
| format | Article |
| id | doaj.art-4b0c17ec936c4bf6975419f37eaf6b91 |
| institution | Directory Open Access Journal |
| issn | 2193-1127 |
| language | English |
| last_indexed | 2024-12-12T11:46:28Z |
| publishDate | 2022-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EPJ Data Science |
| spelling | doaj.art-4b0c17ec936c4bf6975419f37eaf6b912022-12-22T00:25:26ZengSpringerOpenEPJ Data Science2193-11272022-06-0111111210.1140/epjds/s13688-022-00347-5Consensus formation on heterogeneous networksEdoardo Fadda0Junda He1Claudio J. Tessone2Paolo Barucca3Department of Mathematical Sciences, Politecnico di TorinoInformation Systems and Technology Cluster, School of Computing and Information Systems, Singapore Management UniversityBlockchain & Distributed Ledger Technologies Group, Informatics Department, University of ZurichDepartment of Computer Science, UCLAbstract Reaching consensus—a macroscopic state where the system constituents display the same microscopic state—is a necessity in multiple complex socio-technical and techno-economic systems: their correct functioning ultimately depends on it. In many distributed systems—of which blockchain-based applications are a paradigmatic example—the process of consensus formation is crucial not only for the emergence of a leading majority but for the very functioning of the system. We build a minimalistic network model of consensus formation on blockchain systems for quantifying how central nodes—with respect to their average distance to others—can leverage on their position to obtain competitive advantage in the consensus process. We show that in a wide range of network topologies, the probability of forming a majority can significantly increase depending on the centrality of nodes that initiate the spreading. Further, we study the role that network topology plays on the consensus process: we show that central nodes in scale-free networks can win consensus in the network even if they broadcast states significantly later than peripheral ones.https://doi.org/10.1140/epjds/s13688-022-00347-5Network theoryDistributed systemsConsensus formation |
| spellingShingle | Edoardo Fadda Junda He Claudio J. Tessone Paolo Barucca Consensus formation on heterogeneous networks EPJ Data Science Network theory Distributed systems Consensus formation |
| title | Consensus formation on heterogeneous networks |
| title_full | Consensus formation on heterogeneous networks |
| title_fullStr | Consensus formation on heterogeneous networks |
| title_full_unstemmed | Consensus formation on heterogeneous networks |
| title_short | Consensus formation on heterogeneous networks |
| title_sort | consensus formation on heterogeneous networks |
| topic | Network theory Distributed systems Consensus formation |
| url | https://doi.org/10.1140/epjds/s13688-022-00347-5 |
| work_keys_str_mv | AT edoardofadda consensusformationonheterogeneousnetworks AT jundahe consensusformationonheterogeneousnetworks AT claudiojtessone consensusformationonheterogeneousnetworks AT paolobarucca consensusformationonheterogeneousnetworks |