Publication: Large-scale behavior of end-to-end epidemic message loss recovery1
dc.contributor.coauthor | N/A | |
dc.contributor.department | Department of Computer Engineering | |
dc.contributor.kuauthor | Özkasap, Öznur | |
dc.contributor.kuprofile | Faculty Member | |
dc.contributor.other | Department of Computer Engineering | |
dc.contributor.schoolcollegeinstitute | College of Engineering | |
dc.contributor.yokid | 113507 | |
dc.date.accessioned | 2024-11-09T23:35:30Z | |
dc.date.issued | 2002 | |
dc.description.abstract | An important class of large-scale distributed applications is insensitive to small inconsistencies among participants, as long as these events are temporary and not frequent. An efficient way for propagating information to participants in such cases is referred to as epidemic protocols. Epidemic protocols are simple, scale well and robust again common failures, and provide eventual consistency as well. They combine benefits of efficiency in hierarchical data dissemination with robustness in flooding protocols. These communication mechanisms have been mainly used for resolving inconsistencies in distributed database updates, failure detection, message loss recovery in multicast communication, network news distribution, group membership management, scalable system management, and resource discovery. In this paper, we focus on an end-to-end epidemic loss recovery mechanism for multicasting and give our simulation results discussing the performance of the approach in large-scale network settings. | |
dc.description.indexedby | Scopus | |
dc.description.openaccess | YES | |
dc.description.publisherscope | International | |
dc.description.sponsorship | IBM | |
dc.description.sponsorship | SIEMENS | |
dc.description.sponsorship | swisscom | |
dc.description.sponsorship | TIK | |
dc.description.volume | 2511 | |
dc.identifier.doi | 10.1007/3-540-45859-x_3 | |
dc.identifier.isbn | 9783-5404-4356-8 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.link | https://www.scopus.com/inward/record.uri?eid=2-s2.0-35248812385anddoi=10.1007%2f3-540-45859-x_3andpartnerID=40andmd5=adf1637a57d9a1806b4927a32783837f | |
dc.identifier.quartile | Q4 | |
dc.identifier.scopus | 2-s2.0-35248812385 | |
dc.identifier.uri | http://dx.doi.org/10.1007/3-540-45859-x_3 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14288/12513 | |
dc.keywords | Bimodal multicast | |
dc.keywords | End-toend protocols | |
dc.keywords | Epidemic communication | |
dc.keywords | Loss recovery | |
dc.keywords | Scalable multicast | |
dc.keywords | Computer system recovery | |
dc.keywords | Distributed computer systems | |
dc.keywords | Distributed database systems | |
dc.keywords | Epidemiology | |
dc.keywords | Multicasting | |
dc.keywords | Recovery | |
dc.keywords | Web services | |
dc.keywords | Communication mechanisms | |
dc.keywords | Distributed database | |
dc.keywords | Eventual consistency | |
dc.keywords | Large-scale distributed applications | |
dc.keywords | Large-scale network | |
dc.keywords | Loss recovery | |
dc.keywords | Multicast communication | |
dc.keywords | Scalable multicast | |
dc.keywords | Quality of service | |
dc.language | English | |
dc.publisher | Springer | |
dc.source | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | |
dc.subject | Computer engineering | |
dc.title | Large-scale behavior of end-to-end epidemic message loss recovery1 | |
dc.type | Conference proceeding | |
dspace.entity.type | Publication | |
local.contributor.authorid | 0000-0003-4343-0986 | |
local.contributor.kuauthor | Özkasap, Öznur | |
relation.isOrgUnitOfPublication | 89352e43-bf09-4ef4-82f6-6f9d0174ebae | |
relation.isOrgUnitOfPublication.latestForDiscovery | 89352e43-bf09-4ef4-82f6-6f9d0174ebae |