A data transmission approach with energy reduction based on virtual machine migration technique in cloud computing. (4th November 2022)

• Record Type: Journal Article
• Authors: Basha, H. Anwar; Saravanakumar, R.; Prabu, K.; Mishra, Divyendu Kumar; Narayanan, S.; Samydurai, A.
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 14:Number 1(2023)
• Page Start: 43
• Page End: 51
• Publication Date: 2022-11-04
• Subjects: virtual machine -- VM migration -- data sharing -- evolutionary computing; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

Abstract

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.