A data transmission approach with energy reduction based on virtual machine migration technique in cloud computing

被引:0
|
作者
Basha, H. Anwar [1 ]
Saravanakumar, R. [2 ]
Prabu, K. [3 ]
Mishra, Divyendu Kumar [4 ]
Narayanan, S. [5 ]
Samydurai, A. [6 ]
机构
[1] Reva Univ, Sch Comp Sci & Engn, Bengaluru, India
[2] Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Inst Elect & Commun Engn, Dept Wireless Commun, Chennai, Tamil Nadu, India
[3] Sudharsan Coll Arts & Sci, PG & Res Dept Comp Sci, Pudukkottai, Tamil Nadu, India
[4] VBS Purvanchal Univ, Fac Engn, Dept Comp Sci & Engn, Jaunpur, Uttar Pradesh, India
[5] SRM Valliammai Engn Coll, Dept Informat Technol, Kattankulathur, Tamil Nadu, India
[6] SRM Valliammai Engn Coll, Dept Comp Sci & Engn, Kattankulathur, Tamil Nadu, India
关键词
virtual machine; VM migration; data sharing; evolutionary computing;
D O I
10.1504/IJESMS.2023.127393
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To provide quicker data access, database centres use virtual machines (VMs) migration to maintain regular content pages in the necessary unit. Memory sharing without downtime is ideal for offline VM migration. However, it has several problems while migrating active VMs. To improve bandwidth availability and hardware stability, it is utilised in workload balancing, low energy retains, and dynamic VM resizing. Thus, needless memory (dirty pages) moving leads in lengthy migration time and downtime. To minimise energy usage and the number of VM migration stages, we offer the NPA-FLI-EC. It combines neural prior prediction algorithm and fuzzy logic insertion of energy reduction on VMM method. Using NPA-FLI-EC, it may optimise VM placement and minimise connection loss on physical servers, while anticipating resource identification from each host reduces needless VM migrations. Thus, it allows for task diversification over multiple servers while saving 2/3 of total energy usage. It also saves bandwidth and improves energy efficiency by consolidating the number of VMs.
引用
收藏
页码:43 / 51
页数:10
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