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PARSEC: an adaptive and efficient platform for reducing cold start in serverless computing

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dc.contributor.authorBuitrago, Nicolás
dc.contributor.authorCamacho, Hector
dc.contributor.authorJimeno, Miguel
dc.contributor.authorViloria Núñez, Cesar Augusto
dc.contributor.authorCardona, Jairo
dc.contributor.authorSalazar, Augusto
dc.contributor.researchgroupGrupo de Investigación Tecnologías Aplicadas y Sistemas de Información (GRITAS)
dc.date.accessioned2025-12-10T18:19:52Z
dc.date.issued2021-08-08
dc.descriptionContiene ilustraciones, gráficos
dc.description.abstractServerless computing has revolutionized application development but faces a significant challenge: cold starts, which introduce delays when a function is called after a period of inactivity. Addressing these delays is crucial because they affect efficiency, performance, cost, and scalability. Existing mitigation strategies come with trade-offs, such as increased resource overhead and the need for precise resource management predictions. Also, optimizing the function startup process requires detailed knowledge of the runtime characteristics and the isolation technique used, such as using a container-based or a micro virtual machine setup. This work presents PARSEC, a comprehensive solution for cold start issues in serverless computing. By focusing on reducing initialization latency in idle containers, this research seeks to preserve scalability and ease of deployment features of serverless computing while overcoming cold start limitations. The proposed architecture improved cold start by streamlining the initialization of containers to reduce overhead. This involves minimizing unnecessary operations and customizing launches for serverless needs, aiming for a faster and more efficient setup. It also enhances the provisioning of Zygotes to speed up sandbox launches. The results show better performance for PARSEC when compared with other architectures, particularly at shorter wait times, suggesting effective cold start management. The strategic management of Zygotes and their provisioning scaling plays a critical role in managing large numbers of packages and instances, thereby enhancing the performance of package management. The cache system also evolves to become more selective, reducing overhead by focusing on essential packages
dc.format.extent14
dc.format.mimetypeapplication/pdf
dc.identifier.citationN. Buitrago et al., "PARSEC: an Adaptive and Efficient Platform for Reducing Cold Start in Serverless Computing" in IEEE Transactions on Services Computing, vol. , no. 01, pp. 1-14, PrePrints 5555, doi: 10.1109/TSC.2025.3627934.
dc.identifier.urihttps://hdl.handle.net/20.500.12585/14289
dc.language.isoeng
dc.publisherIEEE Transactions on Services Computing
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dc.rights.licenseAtribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subject.ddc000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadores
dc.subject.lembCloud computing
dc.subject.lembDistributed computing
dc.subject.lembSoftware architecture
dc.subject.lembComputación en la nube
dc.subject.lembArquitectura de computadores
dc.subject.ocde1. Ciencias Naturales::1B. Computación y ciencias de la información::1B01. Ciencias de la computación
dc.subject.odsODS 9: Industria, innovación e infraestructura. Construir infraestructuras resilientes, promover la industrialización inclusiva y sostenible y fomentar la innovación
dc.subject.proposalContainers
dc.subject.proposalRuntime
dc.subject.proposalServerless Computing,
dc.subject.proposalDelays
dc.subject.proposalScalability
dc.subject.proposalCosts
dc.subject.proposalLoading
dc.subject.proposalComplexity Theory
dc.subject.proposalPrevention And Mitigation
dc.subject.proposalLoad Modeling
dc.subject.proposalArticle Submission
dc.subject.proposalIEEE
dc.subject.proposalIEE Etran
dc.subject.proposalJournal
dc.subject.proposalLATEX
dc.subject.proposalPaper
dc.subject.proposalTemplate
dc.subject.proposalTypesetting
dc.subject.proposalScalable
dc.subject.proposalProvisioning
dc.subject.proposalCold Start
dc.subject.proposalResponse Time
dc.subject.proposalTree Structure
dc.subject.proposalC Group
dc.subject.proposalWaiting Time
dc.subject.proposalOpen Platform
dc.subject.proposalSecurity Risks
dc.subject.proposalAndroid Application
dc.subject.proposalVirtual Machines,
dc.subject.proposalFile System
dc.subject.proposalKept Alive
dc.subject.proposalAverage Response Time
dc.subject.proposalStatus Code
dc.subject.proposalError Handling
dc.subject.proposalResource Contention
dc.subject.proposalEssential Package
dc.subject.proposalPackage Manager
dc.titlePARSEC: an adaptive and efficient platform for reducing cold start in serverless computingeng
dc.typeArtículo de revista
dc.type.coarhttp://purl.org/coar/resource_type/c_18cf
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.contentText
dc.type.driverinfo:eu-repo/semantics/article
dc.type.redcolhttp://purl.org/redcol/resource_type/ART
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryef7ccd85-aebf-4b7b-abb0-662939e5bd77

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