Fine-Grained, Adaptive Resource Sharing for Real Pay-Per-Use Pricing in Clouds
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Young Choon | - |
dc.contributor.author | Kim, Youngjin | - |
dc.contributor.author | Han, Hyuck | - |
dc.contributor.author | Kang, Sooyong | - |
dc.date.accessioned | 2022-07-15T21:05:29Z | - |
dc.date.available | 2022-07-15T21:05:29Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2015-09 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/156415 | - |
dc.description.abstract | Cloud computing is characterized by its essentially pay-per-use pricing with elasticity. Typically, the granularity of usage for such pricing is at virtual machine (VM) level in IaaS clouds, e.g., a multiple of machine hours. The elasticity and cost effectiveness in these clouds are primarily achieved through the exploitation of resource virtualization and sharing. However, a majority of applications running on VMs in clouds struggle to fully utilize resources allocated to them. Since co-location granularity is strictly restricted to VM level and resources allocated to VMs are space-shared, the unused resources are apt to be wasted while users are still charged for such wastage. In this paper, we address the problem of fine-grained and adaptive resource sharing for real pay-per-use pricing. To this end, we devise a resource management mechanism as a cost efficiency solution for both users and providers of clouds. The mechanism consists of a container-based resource allocator and a real-usage based pricing scheme. We demonstrate the efficacy of this mechanism via experiments, in Amazon EC2, using two typical workloads in clouds, web services and database services, and a compute-intensive high energy physics application. Our results show that the mechanism can achieve near-optimal cost efficiency. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Fine-Grained, Adaptive Resource Sharing for Real Pay-Per-Use Pricing in Clouds | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Sooyong | - |
dc.identifier.doi | 10.1109/ICCAC.2015.36 | - |
dc.identifier.scopusid | 2-s2.0-84962124346 | - |
dc.identifier.bibliographicCitation | Proceedings - 2015 International Conference on Cloud and Autonomic Computing, ICCAC 2015, pp.236 - 243 | - |
dc.relation.isPartOf | Proceedings - 2015 International Conference on Cloud and Autonomic Computing, ICCAC 2015 | - |
dc.citation.title | Proceedings - 2015 International Conference on Cloud and Autonomic Computing, ICCAC 2015 | - |
dc.citation.startPage | 236 | - |
dc.citation.endPage | 243 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordPlus | Cloud computing | - |
dc.subject.keywordPlus | Containers | - |
dc.subject.keywordPlus | Cost effectiveness | - |
dc.subject.keywordPlus | Elasticity | - |
dc.subject.keywordPlus | High energy physics | - |
dc.subject.keywordPlus | Web services | - |
dc.subject.keywordPlus | containerization | - |
dc.subject.keywordPlus | Database service | - |
dc.subject.keywordPlus | Pay-per-use | - |
dc.subject.keywordPlus | Resource allocator | - |
dc.subject.keywordPlus | Resource management | - |
dc.subject.keywordPlus | Resource sharing | - |
dc.subject.keywordPlus | Resource Virtualization | - |
dc.subject.keywordPlus | Virtual machines | - |
dc.subject.keywordPlus | Costs | - |
dc.subject.keywordAuthor | Cloud computing | - |
dc.subject.keywordAuthor | containerization | - |
dc.subject.keywordAuthor | fine-grained resource sharing | - |
dc.subject.keywordAuthor | pay-per-use pricing | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/7312164 | - |
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