An Adaptive Push-Pull for Disseminating Dynamic Workload and Virtual Machine Live Migration in Cloud Computing

IF 0.6 Q4 COMPUTER SCIENCE, THEORY & METHODS International Journal of Grid and High Performance Computing Pub Date : 2022-01-01 DOI:10.4018/ijghpc.301591
K. Naik
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引用次数: 3

Abstract

Adapting a dynamic load dissemination system for distributed computing pasture has become a hot spot problem of current research. In the instance of overloaded VM’s or node failure, the associated resources face difficult to determine which VM should be selected for load exchanging and/or how many VM’s should migrate to manage load imbalance. This work, introduces a Hierarchical Adaptive Push-Pull system for disseminating dynamic workload and live migration of VM’s among resources in the Cloud. Adhering to the Adaptive Push-Pull, Cloud Resources frequently pull’s the workload or through VM Managers based on load dynamics. In contrast, status information pertaining to Cloud Resources maintained by the Cloud Resource Managers that possess push capability to push the workload only to those VM’s which are capable enough to receive additional load. These two practices contain balancing possessions through efficient load management complications and simulation result addresses reduced load deviation and scalable resources utilization.
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云计算中动态工作负载传播和虚拟机实时迁移的自适应推拉
为分布式计算牧场采用动态负荷分发系统已成为当前研究的热点问题。在虚拟机过载或节点故障的情况下,相关资源难以确定应该选择哪个虚拟机进行负载交换和/或应该迁移多少虚拟机以管理负载不平衡。本文介绍了一种分层自适应推拉系统,用于在云中的资源之间传播动态工作负载和VM的实时迁移。坚持自适应推拉,云资源经常拉工作负载或通过虚拟机管理器基于负载动态。相反,由云资源管理器维护的与云资源相关的状态信息拥有推送功能,可以将工作负载仅推送到那些有能力接收额外负载的VM。这两个实践包括通过有效的负载管理复杂性来平衡财产,模拟结果解决了减少的负载偏差和可扩展的资源利用率。
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来源期刊
CiteScore
1.70
自引率
10.00%
发文量
24
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