LLRS : A Low Latency Resource Scheduling in Cloud Continuum Orchestration
Uloženo v:
| Název: | LLRS : A Low Latency Resource Scheduling in Cloud Continuum Orchestration |
|---|---|
| Autoři: | Mukuhi, David Kule, Outtagarts, Abdelkader |
| Přispěvatelé: | kule Mukuhi, david |
| Zdroj: | 2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN). :81-87 |
| Informace o vydavateli: | IEEE, 2024. |
| Rok vydání: | 2024 |
| Témata: | machine learning, low latency scheduling, Distributed Orchestration, [INFO] Computer Science [cs], Distributed Orchestration In-memory database low latency scheduling machine learning, In-memory database |
| Popis: | The convergence of Network Function Virtualization (NFV) and Cloud Computing marks a transformative milestone in the telecommunications domain, setting the stage for the realization of 5G/6G flagship technologies. Containers, as a rising virtualization solution, have gained significant traction in recent years due to their attributes like shared host OS, swift launch times, and portability. A central challenge in this landscape is the effective orchestration of resources within cloud continuum infrastructure, ensuring seamless service operation. The abstraction of network services through NFV and the concept of network slicing amplify challenges in resource allocation. Kubernetes and Docker Swarm have emerged as powerful orchestration platforms. However, while widely adopted in application deployment, these solutions must meet the distinctive quality-of-service (QoS) demands of the telecommunications industry like Ultra-reliable low-latency communication. This paper proposes a Low Latency Resource Scheduler (LLRS) for Cloud Continuum. This new scheduling architecture approach leverages inmemory data grid and distributed resource predictions to reduce scheduling delay. Our experiments on heterogeneous environment has shown a reduction of nearly half the time required to schedule container in docker swarm and Kubernetes |
| Druh dokumentu: | Article Conference object |
| Popis souboru: | application/pdf |
| DOI: | 10.1109/icin60470.2024.10494439 |
| Přístupová URL adresa: | https://hal.science/hal-04995146v1 https://hal.science/hal-04995146v1/document https://doi.org/10.1109/icin60470.2024.10494439 |
| Rights: | STM Policy #29 |
| Přístupové číslo: | edsair.doi.dedup.....3c64d00a1cfd8b9cd421c7d5755cc74f |
| Databáze: | OpenAIRE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://explore.openaire.eu/search/publication?articleId=doi_dedup___%3A%3A3c64d00a1cfd8b9cd421c7d5755cc74f Name: EDS - OpenAIRE (s4221598) Category: fullText Text: View record at OpenAIRE – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Mukuhi%20DK Name: ISI Category: fullText Text: Nájsť tento článok vo Web of Science Icon: https://imagesrvr.epnet.com/ls/20docs.gif MouseOverText: Nájsť tento článok vo Web of Science |
|---|---|
| Header | DbId: edsair DbLabel: OpenAIRE An: edsair.doi.dedup.....3c64d00a1cfd8b9cd421c7d5755cc74f RelevancyScore: 979 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 979.438720703125 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: LLRS : A Low Latency Resource Scheduling in Cloud Continuum Orchestration – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mukuhi%2C+David+Kule%22">Mukuhi, David Kule</searchLink><br /><searchLink fieldCode="AR" term="%22Outtagarts%2C+Abdelkader%22">Outtagarts, Abdelkader</searchLink> – Name: Author Label: Contributors Group: Au Data: kule Mukuhi, david – Name: TitleSource Label: Source Group: Src Data: <i>2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN)</i>. :81-87 – Name: Publisher Label: Publisher Information Group: PubInfo Data: IEEE, 2024. – Name: DatePubCY Label: Publication Year Group: Date Data: 2024 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22machine+learning%22">machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22low+latency+scheduling%22">low latency scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+Orchestration%22">Distributed Orchestration</searchLink><br /><searchLink fieldCode="DE" term="%22[INFO]+Computer+Science+[cs]%22">[INFO] Computer Science [cs]</searchLink><br /><searchLink fieldCode="DE" term="%22Distributed+Orchestration+In-memory+database+low+latency+scheduling+machine+learning%22">Distributed Orchestration In-memory database low latency scheduling machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22In-memory+database%22">In-memory database</searchLink> – Name: Abstract Label: Description Group: Ab Data: The convergence of Network Function Virtualization (NFV) and Cloud Computing marks a transformative milestone in the telecommunications domain, setting the stage for the realization of 5G/6G flagship technologies. Containers, as a rising virtualization solution, have gained significant traction in recent years due to their attributes like shared host OS, swift launch times, and portability. A central challenge in this landscape is the effective orchestration of resources within cloud continuum infrastructure, ensuring seamless service operation. The abstraction of network services through NFV and the concept of network slicing amplify challenges in resource allocation. Kubernetes and Docker Swarm have emerged as powerful orchestration platforms. However, while widely adopted in application deployment, these solutions must meet the distinctive quality-of-service (QoS) demands of the telecommunications industry like Ultra-reliable low-latency communication. This paper proposes a Low Latency Resource Scheduler (LLRS) for Cloud Continuum. This new scheduling architecture approach leverages inmemory data grid and distributed resource predictions to reduce scheduling delay. Our experiments on heterogeneous environment has shown a reduction of nearly half the time required to schedule container in docker swarm and Kubernetes – Name: TypeDocument Label: Document Type Group: TypDoc Data: Article<br />Conference object – Name: Format Label: File Description Group: SrcInfo Data: application/pdf – Name: DOI Label: DOI Group: ID Data: 10.1109/icin60470.2024.10494439 – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="https://hal.science/hal-04995146v1" linkWindow="_blank">https://hal.science/hal-04995146v1</link><br /><link linkTarget="URL" linkTerm="https://hal.science/hal-04995146v1/document" linkWindow="_blank">https://hal.science/hal-04995146v1/document</link><br /><link linkTarget="URL" linkTerm="https://doi.org/10.1109/icin60470.2024.10494439" linkWindow="_blank">https://doi.org/10.1109/icin60470.2024.10494439</link> – Name: Copyright Label: Rights Group: Cpyrght Data: STM Policy #29 – Name: AN Label: Accession Number Group: ID Data: edsair.doi.dedup.....3c64d00a1cfd8b9cd421c7d5755cc74f |
| PLink | https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsair&AN=edsair.doi.dedup.....3c64d00a1cfd8b9cd421c7d5755cc74f |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/icin60470.2024.10494439 Languages: – Text: Undetermined PhysicalDescription: Pagination: PageCount: 7 StartPage: 81 Subjects: – SubjectFull: machine learning Type: general – SubjectFull: low latency scheduling Type: general – SubjectFull: Distributed Orchestration Type: general – SubjectFull: [INFO] Computer Science [cs] Type: general – SubjectFull: Distributed Orchestration In-memory database low latency scheduling machine learning Type: general – SubjectFull: In-memory database Type: general Titles: – TitleFull: LLRS : A Low Latency Resource Scheduling in Cloud Continuum Orchestration Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mukuhi, David Kule – PersonEntity: Name: NameFull: Outtagarts, Abdelkader – PersonEntity: Name: NameFull: kule Mukuhi, david IsPartOfRelationships: – BibEntity: Dates: – D: 11 M: 03 Type: published Y: 2024 Identifiers: – Type: issn-locals Value: edsair – Type: issn-locals Value: edsairFT Titles: – TitleFull: 2024 27th Conference on Innovation in Clouds, Internet and Networks (ICIN) Type: main |
| ResultId | 1 |
Nájsť tento článok vo Web of Science