Prashan Dharmapala, Lumeshkantha Koneshvaran, Darshanun Sivasooriyathevan, I. Ismail, D. Kasthurirathna
{"title":"点对点分布式计算框架","authors":"Prashan Dharmapala, Lumeshkantha Koneshvaran, Darshanun Sivasooriyathevan, I. Ismail, D. Kasthurirathna","doi":"10.1109/NCTM.2017.7872840","DOIUrl":null,"url":null,"abstract":"Public-Resource Computing (PRC) is an innovative approach to high performance computing that depends on volunteers who contribute their personal computers, where underutilized computing resources are collected and used for computationally intensive research projects. Existing systems basically operate on centralized clusters of nodes to achieve high performance. However, these centralized clusters of nodes can be unrealistic for users who infrequently have a demand of solving large distributed problems. Therefore, large-scale computation time-sharing systems need a decentralized architecture. Peer-to-peer systems are modelled around the assumption that all peers willingly contribute resources to a global pool. This dissertation presents design requirements of sharing the workload among many computational nodes, peer management, and most importantly peer failure management for improving fault tolerance. It represents a Java based peer-to-peer distributed computing framework that allows cross-platform support.","PeriodicalId":343372,"journal":{"name":"2017 6th National Conference on Technology and Management (NCTM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Peer-to-peer distributed computing framework\",\"authors\":\"Prashan Dharmapala, Lumeshkantha Koneshvaran, Darshanun Sivasooriyathevan, I. Ismail, D. Kasthurirathna\",\"doi\":\"10.1109/NCTM.2017.7872840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Public-Resource Computing (PRC) is an innovative approach to high performance computing that depends on volunteers who contribute their personal computers, where underutilized computing resources are collected and used for computationally intensive research projects. Existing systems basically operate on centralized clusters of nodes to achieve high performance. However, these centralized clusters of nodes can be unrealistic for users who infrequently have a demand of solving large distributed problems. Therefore, large-scale computation time-sharing systems need a decentralized architecture. Peer-to-peer systems are modelled around the assumption that all peers willingly contribute resources to a global pool. This dissertation presents design requirements of sharing the workload among many computational nodes, peer management, and most importantly peer failure management for improving fault tolerance. It represents a Java based peer-to-peer distributed computing framework that allows cross-platform support.\",\"PeriodicalId\":343372,\"journal\":{\"name\":\"2017 6th National Conference on Technology and Management (NCTM)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 6th National Conference on Technology and Management (NCTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCTM.2017.7872840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 6th National Conference on Technology and Management (NCTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCTM.2017.7872840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Public-Resource Computing (PRC) is an innovative approach to high performance computing that depends on volunteers who contribute their personal computers, where underutilized computing resources are collected and used for computationally intensive research projects. Existing systems basically operate on centralized clusters of nodes to achieve high performance. However, these centralized clusters of nodes can be unrealistic for users who infrequently have a demand of solving large distributed problems. Therefore, large-scale computation time-sharing systems need a decentralized architecture. Peer-to-peer systems are modelled around the assumption that all peers willingly contribute resources to a global pool. This dissertation presents design requirements of sharing the workload among many computational nodes, peer management, and most importantly peer failure management for improving fault tolerance. It represents a Java based peer-to-peer distributed computing framework that allows cross-platform support.