Publication:
EdgeKV: decentralized, scalable, and consistent storage for the edge

dc.contributor.coauthorAl-Oqily, Ibrahim
dc.contributor.coauthorAloqaily, Moayad
dc.contributor.departmentN/A
dc.contributor.departmentDepartment of Computer Engineering
dc.contributor.kuauthorSonbol, Karim
dc.contributor.kuauthorÖzkasap, Öznur
dc.contributor.kuprofileFaculty Member
dc.contributor.otherDepartment of Computer Engineering
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.yokidN/A
dc.contributor.yokid113507
dc.date.accessioned2024-11-09T11:55:50Z
dc.date.issued2020
dc.description.abstractEdge computing moves the computation closer to the data and the data closer to the user to overcome the high latency communication of cloud computing. Storage at the edge allows data access with high speeds that enable latency-sensitive applications in areas such as autonomous driving and smart grid. However, several distributed services are typically designed for the cloud and building an efficient edge-enabled storage system is challenging because of the distributed and heterogeneous nature of the edge and its limited resources. In this paper, we propose EdgeKV, a decentralized storage system designed for the network edge. EdgeKV offers fast and reliable storage, utilizing data replication with strong consistency guarantees. With a location-transparent and interface-based design, EdgeKV can scale with a heterogeneous system of edge nodes. We implement a prototype of the EdgeKV modules in Golang and evaluate it in both the edge and cloud settings on the Grid’5000 testbed. We utilize the Yahoo! Cloud Serving Benchmark (YCSB) to analyze the system's performance under realistic workloads. Our evaluation results show that EdgeKV outperforms the cloud storage setting with both local and global data access with an average write response time and throughput improvements of 26% and 19% respectively under the same settings. Our evaluations also show that EdgeKV can scale with the number of clients, without sacrificing performance. Finally, we discuss the energy efficiency improvement when utilizing edge resources with EdgeKV instead of a centralized cloud.
dc.description.fulltextYES
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.sponsorshipCollege of Engineering, Al Ain University
dc.description.versionAuthor's final manuscript
dc.description.volume144
dc.formatpdf
dc.identifier.doi10.1016/j.jpdc.2020.05.009
dc.identifier.eissn1096-0848
dc.identifier.embargoNO
dc.identifier.filenameinventorynoIR02911
dc.identifier.issn0743-7315
dc.identifier.linkhttps://doi.org/10.1016/j.jpdc.2020.05.009
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-85085997438
dc.identifier.urihttps://hdl.handle.net/20.500.14288/835
dc.identifier.wos546677400003
dc.keywordsConsistency
dc.keywordsDHT
dc.keywordsDistributed systems
dc.keywordsEdge computing
dc.keywordsKey–value store
dc.languageEnglish
dc.publisherElsevier
dc.relation.grantnoERF-20
dc.relation.urihttp://cdm21054.contentdm.oclc.org/cdm/ref/collection/IR/id/9558
dc.sourceJournal of Parallel and Distributed Computing
dc.subjectComputer science, theory and methods
dc.titleEdgeKV: decentralized, scalable, and consistent storage for the edge
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.authorid0000-0003-4343-0986
local.contributor.kuauthorSonbol, Karim
local.contributor.kuauthorÖzkasap, Öznur
relation.isOrgUnitOfPublication89352e43-bf09-4ef4-82f6-6f9d0174ebae
relation.isOrgUnitOfPublication.latestForDiscovery89352e43-bf09-4ef4-82f6-6f9d0174ebae

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