The cost of reconfiguration in a cloud

Verma, Akshat; Kumar, G. Santhosh; Koller, Ricardo

doi:10.1145/1891719.1891721

Cited by 31 publications

(24 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A possible model for predicting the duration and overhead of live migration was presented by Verma et al [102,103]. According to their findings, migration increases the load of the source PM, but not the load of the target PM.…”

Section: Live Migrationmentioning

confidence: 99%

See 1 more Smart Citation

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

2015

View full text Add to dashboard Cite

Data centers in public, private, and hybrid cloud settings make it possible to provision virtual machines (VMs) with unprecedented flexibility. However, purchasing, operating, and maintaining the underlying physical resources incurs significant monetary costs and also environmental impact. Therefore, cloud providers must optimize the usage of physical resources by a careful allocation of VMs to hosts, continuously balancing between the conflicting requirements on performance and operational costs. In recent years, several algorithms have been proposed for this important optimization problem. Unfortunately, the proposed approaches are hardly comparable because of subtle differences in the used problem models. This paper surveys the used problem formulations and optimization algorithms, highlighting their strengths and limitations, also pointing out the areas that need further research in the future.

show abstract

Section: Live Migrationmentioning

confidence: 99%

“…In the case of VMs mapped on a PM owned by the CP, the VMM (Virtual Machine Monitor) can be instructed to set the resources allocated to the respective VMs as necessary [105,42,102]. In the case of VMs rented from eCPs, it may make sense to re-pack the application into VMs of different size, e.g., into a smaller number of larger VMs.…”

Section: Actions Of the Cpmentioning

confidence: 99%

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

2015

View full text Add to dashboard Cite

show abstract

“…Changing an existing placement can be realized through live-migration, which is resource-intensive [13]. Specifically, moving a VM from one machine to another machine, without interrupting its execution, consumes a significant amount of network bandwidth along the communication path between the two machines.…”

Section: Placement Schedulermentioning

confidence: 99%

Allocating Compute and Network Resources Under Management Objectives in Large-Scale Clouds

2013

View full text Add to dashboard Cite

We consider the problem of jointly allocating compute and network resources in a large Infrastructure-as-a-Service (IaaS) cloud. We formulate the problem of optimally allocating resources to virtual data centers (VDCs) for four well-known management objectives: balanced load, energy efficiency, fair allocation, and service differentiation. Then, we outline an architecture for resource allocation, which centers around a set of cooperating controllers, each solving a problem related to the chosen management objective. We illustrate how a global management objective is mapped onto objectives that govern the execution of these controllers. For a key controller, the Dynamic Placement Controller, we give a detailed distributed design, which is based on a gossip protocol that can switch between management objectives. The design is applicable to a broad class of management objectives, which we characterize through a property of the objective function. The property ensures the applicability of an iterative descent method that the gossip protocol implements. We evaluate, through simulation, the dynamic placement of VDCs for a large cloud under changing load and VDC churn. Simulation results show that this controller is effective and highly scalable, up to 100'000 nodes, for the management objectives considered.

show abstract

“…The pre-copy and stop-and-copy processes require additional resources, particularly, network bandwidth and some CPU cycles. Since co-located virtual machines must not be affected by the migration, there may be a resource deficiency for the VM being migrated [23].…”

Section: Related Workmentioning

confidence: 99%

Investigation into the energy cost of live migration of virtual machines

Rybina

Dargie

Strunk

et al. 2013

2013 Sustainable Internet and ICT for Sustainability (SustainIT)

View full text Add to dashboard Cite

-One of the mechanisms to achieve energy efficiency in virtualized environments is to consolidate the workload (virtual machines) of underutilized servers and to switch-off these servers all together. Similarly, the workloads of overloaded servers can be distributed onto other servers for a load balancing reason. Central to this approach is the migration of virtual machines at runtime, which may introduce its own overhead in terms of energy consumption and service execution latency. This paper experimentally investigates the magnitude of this overhead. We use the Kernel-based Virtual Machine (KVM) hypervisor and a custom-made benchmark for our experiments. We will demonstrate that the workload of a virtual machine does not have any bearing on the power consumption of the destination server during migration but it has on the source server. Moreover, the available network bandwidth and the size of the virtual machine do indeed introduce a non-negligible energy overhead and migration latency on both the source and the destination server.

show abstract

The cost of reconfiguration in a cloud

Cited by 31 publications

References 9 publications

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

Allocating Compute and Network Resources Under Management Objectives in Large-Scale Clouds

Investigation into the energy cost of live migration of virtual machines

Contact Info

Product

Resources

About