Cost-based Virtual Machine Scheduling for Data-as-a-Service
Data-as-a-Service (DaaS) is a branch of cloud computing that supports “querying the Web”. Due to its ultrahigh scale, it is essential to establish rules when defining resources’ costs and guidelines for infrastructure investments. Those decisions should prio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Graz University of Technology
2023-12-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/99223/download/pdf/ |
| _version_ | 1827395073782841344 |
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| author | Ana Cristina Alves de Oliveira Oliveira Marco Aurélio Spohn Christof Fetzer Le Quoc Do André Martin |
| author_facet | Ana Cristina Alves de Oliveira Oliveira Marco Aurélio Spohn Christof Fetzer Le Quoc Do André Martin |
| author_sort | Ana Cristina Alves de Oliveira Oliveira |
| collection | DOAJ |
| description | Data-as-a-Service (DaaS) is a branch of cloud computing that supports “querying the Web”. Due to its ultrahigh scale, it is essential to establish rules when defining resources’ costs and guidelines for infrastructure investments. Those decisions should prioritize minimizing the incidence of agreement breaches that compromise the performance of cloud services and optimize resources’ usage and services’ cost. This article aims to address the cost problem of DaaS by developing a model that optimizes the costs of querying distributed data sources over virtual machines spread across multisite data centers. We have designed and analyzed a cost model for DaaS, besides implementing a scheduling system to perform a cost-based VM assignment. To validate our model, we have studied and characterized a real-world DaaS system’s network and processing workloads. On average, our cost-based scheduling performs at least twice as well as the traditional round-robin approach. Our model also supports load balancing and infrastructure scalability when combined with an adaptive cost scheme that prioritizes VM allocation within the underutilized data centers and avoids sending VMs to data centers in the eminence of becoming over-utilized. |
| first_indexed | 2024-03-08T18:27:39Z |
| format | Article |
| id | doaj.art-5e2696a4e53144fc94899ae1711f30ef |
| institution | Directory Open Access Journal |
| issn | 0948-6968 |
| language | English |
| last_indexed | 2024-03-08T18:27:39Z |
| publishDate | 2023-12-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj.art-5e2696a4e53144fc94899ae1711f30ef2023-12-30T11:00:15ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682023-12-0129121461148110.3897/jucs.9922399223Cost-based Virtual Machine Scheduling for Data-as-a-ServiceAna Cristina Alves de Oliveira Oliveira0Marco Aurélio Spohn1Christof Fetzer2Le Quoc Do3André Martin4Federal Institute of Paraíba (IFPB)Federal University of Fronteira Sul (UFFS)Technical University of DresdenTechnical University of DresdenTechnical University of DresdenData-as-a-Service (DaaS) is a branch of cloud computing that supports “querying the Web”. Due to its ultrahigh scale, it is essential to establish rules when defining resources’ costs and guidelines for infrastructure investments. Those decisions should prioritize minimizing the incidence of agreement breaches that compromise the performance of cloud services and optimize resources’ usage and services’ cost. This article aims to address the cost problem of DaaS by developing a model that optimizes the costs of querying distributed data sources over virtual machines spread across multisite data centers. We have designed and analyzed a cost model for DaaS, besides implementing a scheduling system to perform a cost-based VM assignment. To validate our model, we have studied and characterized a real-world DaaS system’s network and processing workloads. On average, our cost-based scheduling performs at least twice as well as the traditional round-robin approach. Our model also supports load balancing and infrastructure scalability when combined with an adaptive cost scheme that prioritizes VM allocation within the underutilized data centers and avoids sending VMs to data centers in the eminence of becoming over-utilized.https://lib.jucs.org/article/99223/download/pdf/Cloud computingData-as-serviceCloud Cost Model |
| spellingShingle | Ana Cristina Alves de Oliveira Oliveira Marco Aurélio Spohn Christof Fetzer Le Quoc Do André Martin Cost-based Virtual Machine Scheduling for Data-as-a-Service Journal of Universal Computer Science Cloud computing Data-as-service Cloud Cost Model |
| title | Cost-based Virtual Machine Scheduling for Data-as-a-Service |
| title_full | Cost-based Virtual Machine Scheduling for Data-as-a-Service |
| title_fullStr | Cost-based Virtual Machine Scheduling for Data-as-a-Service |
| title_full_unstemmed | Cost-based Virtual Machine Scheduling for Data-as-a-Service |
| title_short | Cost-based Virtual Machine Scheduling for Data-as-a-Service |
| title_sort | cost based virtual machine scheduling for data as a service |
| topic | Cloud computing Data-as-service Cloud Cost Model |
| url | https://lib.jucs.org/article/99223/download/pdf/ |
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