Topology analysis of the Ripple transaction network
The Ripple network is one typical blockchain‐based decentralized credit network, which supports money transfer without physical money movement by only transferring the credits between participants. It is critical to obtain a deep understanding on the characteristics of the payment networks while opt...
Gespeichert in:
Veröffentlicht in: | International journal of network management 2024-03, Vol.34 (2), p.n/a |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | n/a |
---|---|
container_issue | 2 |
container_start_page | |
container_title | International journal of network management |
container_volume | 34 |
creator | Jin, Anan Ye, Yuhang Lee, Brian Qiao, Yuansong |
description | The Ripple network is one typical blockchain‐based decentralized credit network, which supports money transfer without physical money movement by only transferring the credits between participants. It is critical to obtain a deep understanding on the characteristics of the payment networks while optimizing the network design and transaction routing. This paper presents a comprehensive analysis to the Ripple transaction network, including two subnets formed by the two key functionalities, that is, Ripple Direct Payment Network (RDPN) and Ripple Credit Payment Network (RCPN). The analysis is performed with different network metrics, including clustering coefficient, centrality, and so on. Furthermore, this paper provides an in‐depth analysis on the node degrees and edge weights, which reflect the number of transacted accounts of an account and the number of transactions between two accounts. The results show that the network is highly imbalanced and concentrated with a few nodes and edges holding most of the resources. Moreover, RDPN and RCPN show different characteristics in terms of transmitted and received transactions, the senders are more concentrated in RDPN, whereas in RCPN, the receivers are more concentrated.
The topologies of two major categories of Ripple transactions, namely, direct payments and credit payments, have been analysed using diverse metrics. The findings reveal significant imbalances and concentrations within these networks, where a small number of nodes dominate the resources. The types of these influential accounts are subsequently presented. |
doi_str_mv | 10.1002/nem.2253 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2954640682</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2954640682</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3423-e8cb12e39c4f6b0cc91c73c941b01e7f38bb7f81012328ee3b8f70f05c38a88f3</originalsourceid><addsrcrecordid>eNp10E1LAzEQgOEgCtYq-BMWvHjZOpPsR3KUUqtQFaSeQzZMdOt2syZbyv57t9arp5nDwzC8jF0jzBCA37W0nXGeixM2QVAqRVRwetjzPC0xk-fsIsYNjBRVOWFi7Tvf-I8hMa1phljHxLuk_6Tkre66hpI-mDYa29e-TVrq9z58XbIzZ5pIV39zyt4fFuv5Y7p6XT7N71epFRkXKUlbISehbOaKCqxVaEthVYYVIJVOyKoqnURALrgkEpV0JTjIrZBGSiem7OZ4twv-e0ex1xu_C-ObUXOVZ0UGheSjuj0qG3yMgZzuQr01YdAI-pBEj0n0IclI0yPd1w0N_zr9snj-9T9hjmE7</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2954640682</pqid></control><display><type>article</type><title>Topology analysis of the Ripple transaction network</title><source>Wiley Journals</source><creator>Jin, Anan ; Ye, Yuhang ; Lee, Brian ; Qiao, Yuansong</creator><creatorcontrib>Jin, Anan ; Ye, Yuhang ; Lee, Brian ; Qiao, Yuansong</creatorcontrib><description>The Ripple network is one typical blockchain‐based decentralized credit network, which supports money transfer without physical money movement by only transferring the credits between participants. It is critical to obtain a deep understanding on the characteristics of the payment networks while optimizing the network design and transaction routing. This paper presents a comprehensive analysis to the Ripple transaction network, including two subnets formed by the two key functionalities, that is, Ripple Direct Payment Network (RDPN) and Ripple Credit Payment Network (RCPN). The analysis is performed with different network metrics, including clustering coefficient, centrality, and so on. Furthermore, this paper provides an in‐depth analysis on the node degrees and edge weights, which reflect the number of transacted accounts of an account and the number of transactions between two accounts. The results show that the network is highly imbalanced and concentrated with a few nodes and edges holding most of the resources. Moreover, RDPN and RCPN show different characteristics in terms of transmitted and received transactions, the senders are more concentrated in RDPN, whereas in RCPN, the receivers are more concentrated.
The topologies of two major categories of Ripple transactions, namely, direct payments and credit payments, have been analysed using diverse metrics. The findings reveal significant imbalances and concentrations within these networks, where a small number of nodes dominate the resources. The types of these influential accounts are subsequently presented.</description><identifier>ISSN: 1055-7148</identifier><identifier>EISSN: 1099-1190</identifier><identifier>DOI: 10.1002/nem.2253</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc</publisher><subject>blockchain ; Clustering ; credit network ; Cryptography ; Design optimization ; Network design ; network topology ; payment network ; Ripple ; Topology</subject><ispartof>International journal of network management, 2024-03, Vol.34 (2), p.n/a</ispartof><rights>2023 John Wiley & Sons Ltd.</rights><rights>2024 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c3423-e8cb12e39c4f6b0cc91c73c941b01e7f38bb7f81012328ee3b8f70f05c38a88f3</cites><orcidid>0000-0002-4157-9018</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fnem.2253$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fnem.2253$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Jin, Anan</creatorcontrib><creatorcontrib>Ye, Yuhang</creatorcontrib><creatorcontrib>Lee, Brian</creatorcontrib><creatorcontrib>Qiao, Yuansong</creatorcontrib><title>Topology analysis of the Ripple transaction network</title><title>International journal of network management</title><description>The Ripple network is one typical blockchain‐based decentralized credit network, which supports money transfer without physical money movement by only transferring the credits between participants. It is critical to obtain a deep understanding on the characteristics of the payment networks while optimizing the network design and transaction routing. This paper presents a comprehensive analysis to the Ripple transaction network, including two subnets formed by the two key functionalities, that is, Ripple Direct Payment Network (RDPN) and Ripple Credit Payment Network (RCPN). The analysis is performed with different network metrics, including clustering coefficient, centrality, and so on. Furthermore, this paper provides an in‐depth analysis on the node degrees and edge weights, which reflect the number of transacted accounts of an account and the number of transactions between two accounts. The results show that the network is highly imbalanced and concentrated with a few nodes and edges holding most of the resources. Moreover, RDPN and RCPN show different characteristics in terms of transmitted and received transactions, the senders are more concentrated in RDPN, whereas in RCPN, the receivers are more concentrated.
The topologies of two major categories of Ripple transactions, namely, direct payments and credit payments, have been analysed using diverse metrics. The findings reveal significant imbalances and concentrations within these networks, where a small number of nodes dominate the resources. The types of these influential accounts are subsequently presented.</description><subject>blockchain</subject><subject>Clustering</subject><subject>credit network</subject><subject>Cryptography</subject><subject>Design optimization</subject><subject>Network design</subject><subject>network topology</subject><subject>payment network</subject><subject>Ripple</subject><subject>Topology</subject><issn>1055-7148</issn><issn>1099-1190</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp10E1LAzEQgOEgCtYq-BMWvHjZOpPsR3KUUqtQFaSeQzZMdOt2syZbyv57t9arp5nDwzC8jF0jzBCA37W0nXGeixM2QVAqRVRwetjzPC0xk-fsIsYNjBRVOWFi7Tvf-I8hMa1phljHxLuk_6Tkre66hpI-mDYa29e-TVrq9z58XbIzZ5pIV39zyt4fFuv5Y7p6XT7N71epFRkXKUlbISehbOaKCqxVaEthVYYVIJVOyKoqnURALrgkEpV0JTjIrZBGSiem7OZ4twv-e0ex1xu_C-ObUXOVZ0UGheSjuj0qG3yMgZzuQr01YdAI-pBEj0n0IclI0yPd1w0N_zr9snj-9T9hjmE7</recordid><startdate>202403</startdate><enddate>202403</enddate><creator>Jin, Anan</creator><creator>Ye, Yuhang</creator><creator>Lee, Brian</creator><creator>Qiao, Yuansong</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-4157-9018</orcidid></search><sort><creationdate>202403</creationdate><title>Topology analysis of the Ripple transaction network</title><author>Jin, Anan ; Ye, Yuhang ; Lee, Brian ; Qiao, Yuansong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3423-e8cb12e39c4f6b0cc91c73c941b01e7f38bb7f81012328ee3b8f70f05c38a88f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>blockchain</topic><topic>Clustering</topic><topic>credit network</topic><topic>Cryptography</topic><topic>Design optimization</topic><topic>Network design</topic><topic>network topology</topic><topic>payment network</topic><topic>Ripple</topic><topic>Topology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jin, Anan</creatorcontrib><creatorcontrib>Ye, Yuhang</creatorcontrib><creatorcontrib>Lee, Brian</creatorcontrib><creatorcontrib>Qiao, Yuansong</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International journal of network management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jin, Anan</au><au>Ye, Yuhang</au><au>Lee, Brian</au><au>Qiao, Yuansong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Topology analysis of the Ripple transaction network</atitle><jtitle>International journal of network management</jtitle><date>2024-03</date><risdate>2024</risdate><volume>34</volume><issue>2</issue><epage>n/a</epage><issn>1055-7148</issn><eissn>1099-1190</eissn><abstract>The Ripple network is one typical blockchain‐based decentralized credit network, which supports money transfer without physical money movement by only transferring the credits between participants. It is critical to obtain a deep understanding on the characteristics of the payment networks while optimizing the network design and transaction routing. This paper presents a comprehensive analysis to the Ripple transaction network, including two subnets formed by the two key functionalities, that is, Ripple Direct Payment Network (RDPN) and Ripple Credit Payment Network (RCPN). The analysis is performed with different network metrics, including clustering coefficient, centrality, and so on. Furthermore, this paper provides an in‐depth analysis on the node degrees and edge weights, which reflect the number of transacted accounts of an account and the number of transactions between two accounts. The results show that the network is highly imbalanced and concentrated with a few nodes and edges holding most of the resources. Moreover, RDPN and RCPN show different characteristics in terms of transmitted and received transactions, the senders are more concentrated in RDPN, whereas in RCPN, the receivers are more concentrated.
The topologies of two major categories of Ripple transactions, namely, direct payments and credit payments, have been analysed using diverse metrics. The findings reveal significant imbalances and concentrations within these networks, where a small number of nodes dominate the resources. The types of these influential accounts are subsequently presented.</abstract><cop>Chichester</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/nem.2253</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0002-4157-9018</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1055-7148 |
ispartof | International journal of network management, 2024-03, Vol.34 (2), p.n/a |
issn | 1055-7148 1099-1190 |
language | eng |
recordid | cdi_proquest_journals_2954640682 |
source | Wiley Journals |
subjects | blockchain Clustering credit network Cryptography Design optimization Network design network topology payment network Ripple Topology |
title | Topology analysis of the Ripple transaction network |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T20%3A54%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Topology%20analysis%20of%20the%20Ripple%20transaction%20network&rft.jtitle=International%20journal%20of%20network%20management&rft.au=Jin,%20Anan&rft.date=2024-03&rft.volume=34&rft.issue=2&rft.epage=n/a&rft.issn=1055-7148&rft.eissn=1099-1190&rft_id=info:doi/10.1002/nem.2253&rft_dat=%3Cproquest_cross%3E2954640682%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2954640682&rft_id=info:pmid/&rfr_iscdi=true |