Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame
The industry and government have recently acknowledged and used virtual machines (VM) to promote their businesses. During the process of VM, some problems might occur. The issues, such as a heavy load of memory, a large load of CPU, a massive load of a disk, a high load of network and time-defined...
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| Format: | Article |
| Language: | English |
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Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)
2023-06-01
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| Series: | Journal of Applied Engineering and Technological Science |
| Subjects: | |
| Online Access: | http://www.yrpipku.com/journal/index.php/jaets/article/view/1646 |
| _version_ | 1797737170283266048 |
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| author | Taufik Hidayat Kalamullah Ramli R. Deiny Mardian Rahutomo Mahardiko |
| author_facet | Taufik Hidayat Kalamullah Ramli R. Deiny Mardian Rahutomo Mahardiko |
| author_sort | Taufik Hidayat |
| collection | DOAJ |
| description |
The industry and government have recently acknowledged and used virtual machines (VM) to promote their businesses. During the process of VM, some problems might occur. The issues, such as a heavy load of memory, a large load of CPU, a massive load of a disk, a high load of network and time-defined migration, might interrupt the business processes. This paper identifies the migration process among hosts for VM to overcome the problem within the defined time frame of migration. The introduction of VMs migration in a timely manner is to detect a problem earlier. There are workload parameters, such as network, CPU, disk and memory as our parameters. To overcome the issue, we have to follow the Model named Fuzzy rule. The rule follows the basic of tree model for decision-making. The application of the fuzzy Model for the study is to determine VMs allocation from busy VMs to vacant VMs for balancing purposes. The result of the study showed that the use of the fuzzy Model to forecast VMs migration based on the defined rule had 2 positive impacts. The positive impacts are (1) Time frame live migration of VMs can reduce workload by 80 %. This aims to reduce failures in performing a live migration of VMs to increase data center performance. (2) In testing, the fuzzy Model can provide results with an accuracy of 90 %, so this model can perform a live migration of VMs precisely in determining the execution time. Next, the workload could be balanced among VMs. This research could be used further to improve 5G Quality of Experience (QoE) shortly.
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| first_indexed | 2024-03-12T13:24:32Z |
| format | Article |
| id | doaj.art-a98a96a8f27e4a7f88df26f07f7703c1 |
| institution | Directory Open Access Journal |
| issn | 2715-6087 2715-6079 |
| language | English |
| last_indexed | 2024-03-12T13:24:32Z |
| publishDate | 2023-06-01 |
| publisher | Yayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI) |
| record_format | Article |
| series | Journal of Applied Engineering and Technological Science |
| spelling | doaj.art-a98a96a8f27e4a7f88df26f07f7703c12023-08-25T11:29:31ZengYayasan Pendidikan Riset dan Pengembangan Intelektual (YRPI)Journal of Applied Engineering and Technological Science2715-60872715-60792023-06-014210.37385/jaets.v4i2.1646Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame Taufik Hidayat0Kalamullah Ramli1R. Deiny Mardian2Rahutomo Mahardiko3Universitas IndonesiaUniversitas IndonesiaUniversitas IndonesiaPT. BFI Finance Indonesia, Tbk The industry and government have recently acknowledged and used virtual machines (VM) to promote their businesses. During the process of VM, some problems might occur. The issues, such as a heavy load of memory, a large load of CPU, a massive load of a disk, a high load of network and time-defined migration, might interrupt the business processes. This paper identifies the migration process among hosts for VM to overcome the problem within the defined time frame of migration. The introduction of VMs migration in a timely manner is to detect a problem earlier. There are workload parameters, such as network, CPU, disk and memory as our parameters. To overcome the issue, we have to follow the Model named Fuzzy rule. The rule follows the basic of tree model for decision-making. The application of the fuzzy Model for the study is to determine VMs allocation from busy VMs to vacant VMs for balancing purposes. The result of the study showed that the use of the fuzzy Model to forecast VMs migration based on the defined rule had 2 positive impacts. The positive impacts are (1) Time frame live migration of VMs can reduce workload by 80 %. This aims to reduce failures in performing a live migration of VMs to increase data center performance. (2) In testing, the fuzzy Model can provide results with an accuracy of 90 %, so this model can perform a live migration of VMs precisely in determining the execution time. Next, the workload could be balanced among VMs. This research could be used further to improve 5G Quality of Experience (QoE) shortly. http://www.yrpipku.com/journal/index.php/jaets/article/view/1646Virtual Machine ServerResource BalancingFuzzy Model5G Quality |
| spellingShingle | Taufik Hidayat Kalamullah Ramli R. Deiny Mardian Rahutomo Mahardiko Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame Journal of Applied Engineering and Technological Science Virtual Machine Server Resource Balancing Fuzzy Model 5G Quality |
| title | Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame |
| title_full | Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame |
| title_fullStr | Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame |
| title_full_unstemmed | Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame |
| title_short | Towards Improving 5G Quality of Experience: Fuzzy as a Mathematical Model to Migrate Virtual Machine Server in The Defined Time Frame |
| title_sort | towards improving 5g quality of experience fuzzy as a mathematical model to migrate virtual machine server in the defined time frame |
| topic | Virtual Machine Server Resource Balancing Fuzzy Model 5G Quality |
| url | http://www.yrpipku.com/journal/index.php/jaets/article/view/1646 |
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