{"title":"支付通道网络 Swift 路由的设计与评估","authors":"Neeraj Sharma , Kalpesh Kapoor , V. Anirudh","doi":"10.1016/j.bcra.2023.100179","DOIUrl":null,"url":null,"abstract":"<div><p>Payment Channel Networks (PCNs) are a promising alternative to improve the scalability of a blockchain network. A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure, thereby sacrificing the ability to confirm transactions instantaneously. PCN uses a routing algorithm to identify a path between two users who do not have a direct channel between them to settle a transaction. The performance of most of the existing centralized path-finding algorithms does not scale with network size. The rapid growth of Bitcoin PCN necessitates considering distributed algorithms. However, the existing decentralized algorithms suffer from resource underutilization. We present a decentralized routing algorithm, Swift, focusing on fee optimization. The concept of a secret path is used to reduce the path length between a sender and a receiver to optimize the fees. Furthermore, we reduce a network structure into combinations of cycles to theoretically study fee optimization with changes in cloud size. The secret path also helps in edge load sharing, which results in an improvement of throughput. Swift routing achieves up to 21% and 63% in fee and throughput optimization, respectively. The results from the simulations follow the trends identified in the theoretical analysis.</p></div>","PeriodicalId":6,"journal":{"name":"ACS Applied Nano Materials","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096720923000544/pdfft?md5=7b1d5eb08e2f11797584988bf124ed9f&pid=1-s2.0-S2096720923000544-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Design and evaluation of Swift routing for payment channel network\",\"authors\":\"Neeraj Sharma , Kalpesh Kapoor , V. Anirudh\",\"doi\":\"10.1016/j.bcra.2023.100179\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Payment Channel Networks (PCNs) are a promising alternative to improve the scalability of a blockchain network. A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure, thereby sacrificing the ability to confirm transactions instantaneously. PCN uses a routing algorithm to identify a path between two users who do not have a direct channel between them to settle a transaction. The performance of most of the existing centralized path-finding algorithms does not scale with network size. The rapid growth of Bitcoin PCN necessitates considering distributed algorithms. However, the existing decentralized algorithms suffer from resource underutilization. We present a decentralized routing algorithm, Swift, focusing on fee optimization. The concept of a secret path is used to reduce the path length between a sender and a receiver to optimize the fees. Furthermore, we reduce a network structure into combinations of cycles to theoretically study fee optimization with changes in cloud size. The secret path also helps in edge load sharing, which results in an improvement of throughput. Swift routing achieves up to 21% and 63% in fee and throughput optimization, respectively. The results from the simulations follow the trends identified in the theoretical analysis.</p></div>\",\"PeriodicalId\":6,\"journal\":{\"name\":\"ACS Applied Nano Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2096720923000544/pdfft?md5=7b1d5eb08e2f11797584988bf124ed9f&pid=1-s2.0-S2096720923000544-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Nano Materials\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2096720923000544\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Nano Materials","FirstCategoryId":"1093","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096720923000544","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Design and evaluation of Swift routing for payment channel network
Payment Channel Networks (PCNs) are a promising alternative to improve the scalability of a blockchain network. A PCN employs off-chain micropayment channels that do not need a global block confirmation procedure, thereby sacrificing the ability to confirm transactions instantaneously. PCN uses a routing algorithm to identify a path between two users who do not have a direct channel between them to settle a transaction. The performance of most of the existing centralized path-finding algorithms does not scale with network size. The rapid growth of Bitcoin PCN necessitates considering distributed algorithms. However, the existing decentralized algorithms suffer from resource underutilization. We present a decentralized routing algorithm, Swift, focusing on fee optimization. The concept of a secret path is used to reduce the path length between a sender and a receiver to optimize the fees. Furthermore, we reduce a network structure into combinations of cycles to theoretically study fee optimization with changes in cloud size. The secret path also helps in edge load sharing, which results in an improvement of throughput. Swift routing achieves up to 21% and 63% in fee and throughput optimization, respectively. The results from the simulations follow the trends identified in the theoretical analysis.
期刊介绍:
ACS Applied Nano Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics and biology relevant to applications of nanomaterials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important applications of nanomaterials.