LaSS: Running Latency Sensitive Serverless Computations at the Edge
Uložené v:
| Názov: | LaSS: Running Latency Sensitive Serverless Computations at the Edge |
|---|---|
| Autori: | Wang, Bin, Ali-Eldin Hassan, Ahmed, 1985, Shenoy, Prashant |
| Zdroj: | 30th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2021, Virtual, Online, Sweden HPDC 2021 - Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing. :239-251 |
| Predmety: | edge computing, function-as-a-service (faas), queueing theory, cloud computing, service-level agreement (sla), serverless computing |
| Popis: | Serverless computing has emerged as a new paradigm for running short-lived computations in the cloud. Due to its ability to handle IoT workloads, there has been considerable interest in running serverless functions at the edge. However, the constrained nature of the edge and the latency sensitive nature of workloads result in many challenges for serverless platforms. In this paper, we present LaSS, a platform that uses model-driven approaches for running latency-sensitive serverless computations on edge resources. LaSS uses principled queuing-based methods to determine an appropriate allocation for each hosted function and auto-scales the allocated resources in response to workload dynamics. LaSS uses a fair-share allocation approach to guarantee a minimum of allocated resources to each function in the presence of overload. In addition, it utilizes resource reclamation methods based on container deflation and termination to reassign resources from over-provisioned functions to under-provisioned ones. We implement a prototype of our approach on an OpenWhisk serverless edge cluster and conduct a detailed experimental evaluation. Our results show that LaSS can accurately predict the resources needed for serverless functions in the presence of highly dynamic workloads, and reprovision container capacity within hundreds of milliseconds while maintaining fair share allocation guarantees. |
| Popis súboru: | electronic |
| Prístupová URL adresa: | https://research.chalmers.se/publication/524945 https://research.chalmers.se/publication/524945/file/524945_Fulltext.pdf |
| Databáza: | SwePub |
Nájsť tento článok vo Web of Science | FullText | Text: Availability: 0 CustomLinks: – Url: https://research.chalmers.se/publication/524945# Name: EDS - SwePub (s4221598) Category: fullText Text: View record in SwePub – Url: https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=EBSCO&SrcAuth=EBSCO&DestApp=WOS&ServiceName=TransferToWoS&DestLinkType=GeneralSearchSummary&Func=Links&author=Wang%20B 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: edsswe DbLabel: SwePub An: edsswe.oai.research.chalmers.se.eaa8ef5f.b963.45c6.8719.d72d948e47b3 RelevancyScore: 926 AccessLevel: 6 PubType: Conference PubTypeId: conference PreciseRelevancyScore: 926.003784179688 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: LaSS: Running Latency Sensitive Serverless Computations at the Edge – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Bin%22">Wang, Bin</searchLink><br /><searchLink fieldCode="AR" term="%22Ali-Eldin+Hassan%2C+Ahmed%22">Ali-Eldin Hassan, Ahmed</searchLink>, 1985<br /><searchLink fieldCode="AR" term="%22Shenoy%2C+Prashant%22">Shenoy, Prashant</searchLink> – Name: TitleSource Label: Source Group: Src Data: <i>30th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2021, Virtual, Online, Sweden HPDC 2021 - Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing</i>. :239-251 – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22edge+computing%22">edge computing</searchLink><br /><searchLink fieldCode="DE" term="%22function-as-a-service+%28faas%29%22">function-as-a-service (faas)</searchLink><br /><searchLink fieldCode="DE" term="%22queueing+theory%22">queueing theory</searchLink><br /><searchLink fieldCode="DE" term="%22cloud+computing%22">cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22service-level+agreement+%28sla%29%22">service-level agreement (sla)</searchLink><br /><searchLink fieldCode="DE" term="%22serverless+computing%22">serverless computing</searchLink> – Name: Abstract Label: Description Group: Ab Data: Serverless computing has emerged as a new paradigm for running short-lived computations in the cloud. Due to its ability to handle IoT workloads, there has been considerable interest in running serverless functions at the edge. However, the constrained nature of the edge and the latency sensitive nature of workloads result in many challenges for serverless platforms. In this paper, we present LaSS, a platform that uses model-driven approaches for running latency-sensitive serverless computations on edge resources. LaSS uses principled queuing-based methods to determine an appropriate allocation for each hosted function and auto-scales the allocated resources in response to workload dynamics. LaSS uses a fair-share allocation approach to guarantee a minimum of allocated resources to each function in the presence of overload. In addition, it utilizes resource reclamation methods based on container deflation and termination to reassign resources from over-provisioned functions to under-provisioned ones. We implement a prototype of our approach on an OpenWhisk serverless edge cluster and conduct a detailed experimental evaluation. Our results show that LaSS can accurately predict the resources needed for serverless functions in the presence of highly dynamic workloads, and reprovision container capacity within hundreds of milliseconds while maintaining fair share allocation guarantees. – Name: Format Label: File Description Group: SrcInfo Data: electronic – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/524945" linkWindow="_blank">https://research.chalmers.se/publication/524945</link><br /><link linkTarget="URL" linkTerm="https://research.chalmers.se/publication/524945/file/524945_Fulltext.pdf" linkWindow="_blank">https://research.chalmers.se/publication/524945/file/524945_Fulltext.pdf</link> |
| PLink | https://erproxy.cvtisr.sk/sfx/access?url=https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsswe&AN=edsswe.oai.research.chalmers.se.eaa8ef5f.b963.45c6.8719.d72d948e47b3 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1145/3431379.3460646 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 239 Subjects: – SubjectFull: edge computing Type: general – SubjectFull: function-as-a-service (faas) Type: general – SubjectFull: queueing theory Type: general – SubjectFull: cloud computing Type: general – SubjectFull: service-level agreement (sla) Type: general – SubjectFull: serverless computing Type: general Titles: – TitleFull: LaSS: Running Latency Sensitive Serverless Computations at the Edge Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Bin – PersonEntity: Name: NameFull: Ali-Eldin Hassan, Ahmed – PersonEntity: Name: NameFull: Shenoy, Prashant IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2021 Identifiers: – Type: issn-locals Value: SWEPUB_FREE – Type: issn-locals Value: CTH_SWEPUB Titles: – TitleFull: 30th International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2021, Virtual, Online, Sweden HPDC 2021 - Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing Type: main |
| ResultId | 1 |