使用OpenDayLight控制器的网络辅助虚拟机迁移的编排算法

Shamim Ahmed, B. Martini, M. Gharbaoui, A. Sgambelluri, S. S. Alam
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引用次数: 0

摘要

在过去几年中,软件虚拟化(例如,Hypervisor)的显著进步使得云服务的敏捷部署成为可能,同时,通过跨数据中心(DC)服务器的敏捷虚拟机(VM)操作(例如,启动、快照、克隆和迁移)实现服务器整合操作成为可能。另一方面,这些进步对数据中心基础设施的整体管理提出了新的挑战,因为虚拟机操作在虚拟化中可能比在传统数据中心中更频繁地发生,并且不仅在相关服务器上产生计算负载,而且在连接服务器的所有交换机上产生网络负载。在这种情况下,软件定义网络(SDN)范式为设计融合资源管理系统开辟了新的机会,该系统能够解决云服务的供应问题,同时在VM供应和迁移期间满足足够的网络性能。本文提出了一种有前途的基于sdn的数据中心网络的高级监控和资源分配功能,旨在报告连接指定服务器的可能的合适路径,这些路径可以用于VM迁移。通过这种方式,可以触发网络辅助迁移,根据指定的需求(例如,实时VM迁移的最小延迟)确保足够的VM迁移延迟,同时解决不同的管理目标(例如,网络负载平衡,最小化能耗)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orchestration algorithms for network-assisted virtual machine migrations using OpenDayLight Controller
In the last years, prominent advances in software virtualization (e.g., Hypervisor) have enabled the agile deployment of cloud services and, at the same time, server consolidation operations through agile Virtual Machine (VM) operations (e.g., start-up, snapshot, cloning, and migrations) across Data Center (DC) servers. On the other hand, such advances pose new challenges in the overall management of the DC infrastructure since VM operations may occur much more frequently in virtualized than in legacy DCs and produce not only a computational load on the involved servers, but also a network load on all the switches connecting the servers. In this context, the Software-Defined Network (SDN) paradigm opens up new opportunities to design convergent resource management systems which is able to address the provisioning of cloud services while meeting adequate network performance during VM provisioning and migrations. In this paper, a promising advanced monitoring and resource allocation function for SDN-based DC networks has been proposed aiming at reporting possible suitable paths connecting specified servers that can be exploited for VM migrations. In such a way, network-assisted migrations can be triggered that assure adequate VM migration delays according to specified requirements (e.g., minimum delay for live VM migration) while addressing different management targets (e.g., network load balancing, minimization of energy consumption).
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