Publication:
Decentralized and locality aware replication method for DHT-based P2P storage systems

dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorHassanzadeh-Nazarabadi, Yahya
dc.contributor.kuauthorKüpçü, Alptekin
dc.contributor.kuauthorÖzkasap, Öznur
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T11:43:18Z
dc.date.issued2018
dc.description.abstractSkip Graph, a type of DHT, plays an important role in P2P cloud storage applications, where nodes publicly or privately store, share, and access data. Nowadays P2P storage systems are widely using replication to support data availability, reliability, and maintainability. With replication, the main consideration is determining peers to replicate the data. Traditional replication algorithms are partially randomized and employ rigid assumptions about nodes' distribution. This results in high access delay between nodes and their closest replicas, which degrades the system performance. We propose GLARAS, a dynamic and fully decentralized locality aware replication method for Skip Graph. In contrast to the traditional algorithms, which replicate based on strict assumptions about the distribution of nodes, GLARAS aims to approximate the underlying distribution by interacting with a very small subset of nodes and minimize the average access delay of replication accordingly. To ensure GLARAS performs at its best, we also propose a dynamic fully decentralized landmark-based locality aware name ID assignment namely LANS. This ensures that the nodes' distances in the overlay and the underlying network are consistent with each other. Our extensive experiments and analysis results demonstrate that compared to the best existing decentralized locality aware replication, GLARAS improves the average access delay of public and private replications by about 13% and 17%, respectively. Likewise, in comparison to the best existing decentralized locality aware name ID assignment, LANS improves the locality awareness of name IDs and the end-to-end latency of search queries in Skip Graph with the gains of about 19% and 8%, respectively. The average replication's access delay of a Skip Graph-based P2P storage system that employs GLARAS and LANS has an improvement gain of about 2.7 over the best state-of-the-art algorithms. Since Skip Graph is a DHT, any other DHT-based P2P storage service would benefit from our solution.
dc.description.fulltextYES
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipN/A
dc.description.versionAuthor's final manuscript
dc.description.volume84
dc.identifier.doi10.1016/j.future.2018.02.007
dc.identifier.eissn1872-7115
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR01555
dc.identifier.issn0167-739X
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85042875950
dc.identifier.urihttps://doi.org/10.1016/j.future.2018.02.007
dc.identifier.wos430521600004
dc.keywordsSkip graph
dc.keywordsDistributed hash table
dc.keywordsDHT
dc.keywordsP2P cloud storage
dc.keywordsLocality aware network for DHTs
dc.keywordsReplication
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofFuture Generation Computer Systems
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/8192
dc.subjectComputer science
dc.titleDecentralized and locality aware replication method for DHT-based P2P storage systems
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorKüpçü, Alptekin
local.contributor.kuauthorÖzkasap, Öznur
local.contributor.kuauthorHassanzadeh-Nazarabadi, Yahya
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Computer Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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