umu.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Towards faster response time models for vertical elasticity
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
2014 (Engelska)Ingår i: 2014 IEEE/ACM 7TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC), 2014, s. 560-565Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Resource provisioning in cloud computing is typ- ically coarse-grained. For example, entire CPU cores may be allocated for periods of up to an hour. The Resource-as-a- Service cloud concept has been introduced to improve the efficiency of resource utilization in clouds. In this concept, resources are allocated in terms of CPU core fractions, with granularities of seconds. Such infrastructures could be created using existing technologies such as lightweight virtualization using LXC or by exploiting the Xen hypervisor’s capacity for vertical elasticity. However, performance models for de- termining how much capacity to allocate to each application are currently lacking. To address this deficit, we evaluate two performance models for predicting mean response times: the previously proposed queue length model and the novel inverse model. The models are evaluated using 3 applications under both open and closed system models. The inverse model reacted rapidly and remained stable even with targets as low as 0.5 seconds. 

Ort, förlag, år, upplaga, sidor
2014. s. 560-565
Nationell ämneskategori
Datorsystem
Forskningsämne
administrativ databehandling
Identifikatorer
URN: urn:nbn:se:umu:diva-93798DOI: 10.1109/UCC.2014.86ISI: 000380558700079ISBN: 978-1-4799-7881-6 (tryckt)OAI: oai:DiVA.org:umu-93798DiVA, id: diva2:751209
Konferens
IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC), DEC 08-11, 2014, London, UNITED KINGDOM
Tillgänglig från: 2014-10-01 Skapad: 2014-10-01 Senast uppdaterad: 2018-06-07Bibliografiskt granskad
Ingår i avhandling
1. Autonomous cloud resource provisioning: accounting, allocation, and performance control
Öppna denna publikation i ny flik eller fönster >>Autonomous cloud resource provisioning: accounting, allocation, and performance control
2015 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

The emergence of large-scale Internet services coupled with the evolution of computing technologies such as distributed systems, parallel computing, utility computing, grid, and virtualization has fueled a movement toward a new resource provisioning paradigm called cloud computing. The main appeal of cloud computing lies in its ability to provide a shared pool of infinitely scalable computing resources for cloud services, which can be quickly provisioned and released on-demand with minimal effort. The rapidly growing interest in cloud computing from both the public and industry together with the rapid expansion in scale and complexity of cloud computing resources and the services hosted on them have made monitoring, controlling, and provisioning cloud computing resources at runtime into a very challenging and complex task. This thesis investigates algorithms, models and techniques for autonomously monitoring, controlling, and provisioning the various resources required to meet services’ performance requirements and account for their resource usage.

Quota management mechanisms are essential for controlling distributed shared resources so that services do not exceed their allocated or paid-for budget. Appropriate cloud-wide monitoring and controlling of quotas must be exercised to avoid over- or under-provisioning of resources. To this end, this thesis presents new distributed algorithms that efficiently manage quotas for services running across distributed nodes.

Determining the optimal amount of resources to meet services’ performance requirements is a key task in cloud computing. However, this task is extremely challenging due to multi-faceted issues such as the dynamic nature of cloud environments, the need for supporting heterogeneous services with different performance requirements, the unpredictable nature of services’ workloads, the non-triviality of mapping performance measurements into resources, and resource shortages. Models and techniques that can predict the optimal amount of resources needed to meet service performance requirements at runtime irrespective of variations in workloads are proposed. Moreover, different service differentiation schemes are proposed for managing temporary resource shortages due to, e.g., flash crowds or hardware failures.

In addition, the resources used by services must be accounted for in order to properly bill customers. Thus, monitoring data for running services should be collected and aggregated to maintain a single global state of the system that can be used to generate a single bill for each customer. However, collecting and aggregating such data across geographical distributed locations is challenging because the management task itself may consume significant computing and network resources unless done with care. A consistency and synchronization mechanism that can alleviate this task is proposed.

Ort, förlag, år, upplaga, sidor
Umeå: Umeå University, 2015. s. 39
Serie
Report / UMINF, ISSN 0348-0542 ; 15.10
Nyckelord
cloud computing, distributed infrastructure, monitoring, accounting, performance modeling, service differentiation
Nationell ämneskategori
Datorsystem
Forskningsämne
administrativ databehandling
Identifikatorer
urn:nbn:se:umu:diva-107955 (URN)978-91-7601-334-2 (ISBN)
Disputation
2015-09-28, MA121 (MIT building), Umeå University, Umeå, 10:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2015-09-07 Skapad: 2015-08-31 Senast uppdaterad: 2018-06-07Bibliografiskt granskad

Open Access i DiVA

fulltext(249 kB)426 nedladdningar
Filinformation
Filnamn FULLTEXT01.pdfFilstorlek 249 kBChecksumma SHA-512
b5a92d601f1c8d5397d40288acf9a0947519efdb2099ce919caf12bbc9a46aeebd5293be0e66fda051fbca9d14136da6fbeb8fcb344bb6df0a3be8a7a9acc36c
Typ fulltextMimetyp application/pdf

Övriga länkar

Förlagets fulltext

Personposter BETA

Lakew, Ewnetu BayuhCristian, KleinFrancisco, Hernandez-RodriguezErik, Elmroth

Sök vidare i DiVA

Av författaren/redaktören
Lakew, Ewnetu BayuhCristian, KleinFrancisco, Hernandez-RodriguezErik, Elmroth
Av organisationen
Institutionen för datavetenskap
Datorsystem

Sök vidare utanför DiVA

GoogleGoogle Scholar
Totalt: 426 nedladdningar
Antalet nedladdningar är summan av nedladdningar för alla fulltexter. Det kan inkludera t.ex tidigare versioner som nu inte längre är tillgängliga.

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 492 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf