Network-aware migration control and scheduling of differentiated virtual machine workloads

Stage, Alexander; Setzer, Thomas

doi:10.1109/cloud.2009.5071527

Cited by 109 publications

(53 citation statements)

References 8 publications

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“…Sherif et al [6] present two simulation models that are able to predict migration time to within 90% accuracy for both synthetic and real-world benchmarks running on Xen hypervisor. Stage et al [15] propose a complementary scheme in which network topology aware scheduling models are used for scheduling live VM migrations such that effect of VM migrations on other nodes in the network is reduced.…”

Section: Cost-aware Migration Of Vms and Prediction Of Migration Perfmentioning

confidence: 99%

Remedy: Network-Aware Steady State VM Management for Data Centers

Mann

Gupta

Dutta

et al. 2012

Lecture Notes in Computer Science

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Abstract. Steady state VM management in data centers should be network-aware so that VM migrations do not degrade network performance of other flows in the network, and if required, a VM migration can be intelligently orchestrated to decongest a network hotspot. Recent research in network-aware management of VMs has focused mainly on an optimal network-aware initial placement of VMs and has largely ignored steady state management. In this context, we present the design and implementation of Remedy. Remedy ranks target hosts for a VM migration based on the associated cost of migration, available bandwidth for migration and the network bandwidth balance achieved by a migration. It models the cost of migration in terms of additional network traffic generated during migration.We have implemented Remedy as an OpenFlow controller application that detects the most congested links in the network and migrates a set of VMs in a network-aware manner to decongest these links. Our choice of target hosts ensures that neither the migration traffic nor the flows that get rerouted as a result of migration cause congestion in any part of the network. We validate our cost of migration model on a virtual software testbed using real VM migrations. Our simulation results using real data center traffic data demonstrate that selective network aware VM migrations can help reduce unsatisfied bandwidth by up to 80-100%.

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Section: Cost-aware Migration Of Vms and Prediction Of Migration Perfmentioning

confidence: 99%

Remedy: Network-Aware Steady State VM Management for Data Centers

Mann

Gupta

Dutta

et al. 2012

Lecture Notes in Computer Science

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“…Other research explores live VM migration [14], [40], [46], efficient scale-out service provisioning [41], and the interface presented to the VDC manager and users [32].…”

Section: Related Workmentioning

confidence: 99%

Using Network Knowledge to Improve Workload Performance in Virtualized Data Centers

Erickson

Heller

McKeown

et al. 2014

2014 IEEE International Conference on Cloud Engineering

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Abstract-The scale and expense of modern data centers motivates running them as efficiently as possible. This paper explores how virtualized data center performance can be improved when network traffic and topology data informs VM placement. Our practical heuristics, tested on network-heavy, scale-out workloads in an 80 server cluster, improve overall performance by up to 70% compared to random placement in a multi-tenant configuration.

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“…It first determines the minimum number of nodes that are necessary to host all VMs, and then computes an optimal order of migrations to minimizing the overall reconfiguration time. Reference [15] presents a networkaware migration scheduling algorithm, which tries to minimize the bandwidth usage while holding migration deadlines.…”

Section: Related Workmentioning

confidence: 99%

Reactive Cloud: Consolidating Virtual Machines with Postcopy Live Migration

Hirofuchi

Nakada

Itoh

et al. 2012

IPSJ Online Transactions

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Dynamic consolidation of virtual machines (VMs) through live migration is a promising technology for IaaS datacenters. VMs are dynamically packed onto fewer server nodes, thereby eliminating excessive power consumption. Existing studies on VM consolidation, however, are based on precopy live migration, which requires dozens of seconds to switch the execution hosts of VMs. It is difficult to optimize VM locations quickly on sudden load changes, resulting in serious violations of VM performance criteria. In this paper, we propose an advanced VM consolidation system exploiting postcopy live migration, which greatly alleviates performance degradation. VM locations are reactively optimized in response to ever-changing resource usage. Sudden overloading of server nodes are promptly resolved by quickly switching the execution hosts of VMs. We have developed a prototype of our consolidation system and evaluated its feasibility through experiments. We confirmed that our consolidation system achieved a higher degree of performance assurance than using precopy migration. Our micro benchmark program, designed for the metric of performance assurance, showed that performance degradation was only 12% or less, even for memory-intensive workloads, which was less than half the level of using precopy live migration. The SPECweb benchmark showed that performance degradation was approximately 10%, which was greatly alleviated from the case of using precopy live migration (21%).

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Network-aware migration control and scheduling of differentiated virtual machine workloads

Cited by 109 publications

References 8 publications

Remedy: Network-Aware Steady State VM Management for Data Centers

Remedy: Network-Aware Steady State VM Management for Data Centers

Using Network Knowledge to Improve Workload Performance in Virtualized Data Centers

Reactive Cloud: Consolidating Virtual Machines with Postcopy Live Migration

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