Application-Aware Virtual Machine Placement in Data Centers

Song, Fei; Huang, Daochao; Zhou, Huachun; You, Ilsun

doi:10.1109/imis.2012.119

Cited by 10 publications

(8 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lloyd et al (2014) investigated the problem of virtual resource provisioning and placement of service oriented applications through dynamic scaling in Cloud infrastructures and presented a server load-aware VM placement scheme that improves application performance and reduces resource cost. Similar multi-objective VM placement and migration works can also be found in , , (Wang et al, 2013), and (Song et al, 2012) that target optimization of energy consumption reduction, server resource utilization, and network usage. Given the fact that VM live migrations are costly operations , the above mentioned VM relocation strategies overlook the impact of necessary VM migrations and reconfiguration on hosted applications, physical servers and network devices.…”

Section: Related Workmentioning

confidence: 92%

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

Ferdaus

Murshed

Calheiros

et al. 2017

Journal of Network and Computer Applications

View full text Add to dashboard Cite

Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance bottleneck. This paper addresses networkaware placement of virtual components (computing and data) of multi-tier applications in data centers and formally defines the placement as an optimization problem. The simultaneous placement of Virtual Machines and data blocks aims at reducing the network overhead of the data center network infrastructure. A greedy heuristic is proposed for the on-demand application components placement that localizes network traffic in the data center interconnect. Such optimization helps reducing communication overhead in upper layer network switches that will eventually reduce the overall traffic volume across the data center. This, in turn, will help reducing packet transmission delay, increasing network performance, and minimizing the energy consumption of network components. Experimental results demonstrate performance superiority of the proposed algorithm over other approaches where it outperforms the stateof-the-art network-aware application placement algorithm across all performance metrics by reducing the average network cost up to 67% and network usage at core switches up to 84%, as well as increasing the average number of application deployments up to 18%.

show abstract

Section: Related Workmentioning

confidence: 92%

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

Ferdaus

Murshed

Calheiros

et al. 2017

Journal of Network and Computer Applications

View full text Add to dashboard Cite

show abstract

“…Application-Aware VM Placement in Data Centers Song et al (2012) have presented an applicationaware VM placement problem focusing on energyefficiency and scalability of modern data centers. The authors have pointed out several factors of modern data center management:…”

Section: Application-aware Vm Placement and Migration Strategiesmentioning

confidence: 99%

Network-Aware Virtual Machine Placement and Migration in Cloud Data Centers

Ferdaus

Murshed

Calheiros

et al. 2015

Advances in Systems Analysis, Software Engineering, and High Performance Computing

View full text Add to dashboard Cite

With the pragmatic realization of computing as a utility, Cloud Computing has recently emerged as a highly successful alternative IT paradigm. Cloud providers are deploying large-scale data centers across the globe to meet the Cloud customers' compute, storage, and network resource demands. Efficiency and scalability of these data centers, as well as the performance of the hosted applications' highly depend on the allocations of the data center resources. Very recently, network-aware Virtual Machine (VM) placement and migration is developing as a very promising technique for the optimization of compute-network resource utilization, energy consumption, and network traffic minimization. This chapter presents the relevant background information and a detailed taxonomy that characterizes and classifies the various components of VM placement and migration techniques, as well as an elaborate survey and comparative analysis of the state of the art techniques. Besides highlighting the various aspects and insights of the network-aware VM placement and migration strategies and algorithms proposed by the research community, the survey further identifies the benefits and limitations of the existing techniques and discusses on the future research directions.

show abstract

“…The proposed intelligent VM placement algorithm, called, Greedy VM placement with Two Path Routing (GVMTPR), which takes the communication requirements between VMs as well as the network traffic state into account during the deployment of the VMs . Previous works have investigated how to optimally place VMs [46,67], or select routes by exploiting multipath diversity in the network [27,58], or jointly leveraging both VM placement and routing [42]. In contrast to previous works, the emphasis of our investigation is to fill the gap for a VM placement and traffic routing scheme that is able to do traffic routing traffic so that traffic can be protected against failures in addition to reducing congestion.…”

Section: Vm Placement With Two-path Routingmentioning

confidence: 99%

“…An application-aware virtual machine placement in Data Centers has been proposed in [67] which suggest reducing the number of physical machine and communication distance between VMs using convex optimization theory in a scalable manner. For placing the VMs, this algorithm considers server constraints as well as the dependency relations between the VMs.…”

Section: Network-aware Vm Placementmentioning

confidence: 99%

“…Considering network knowledge for VM placement can increase traffic locality to reduce network bottlenecks and decrease latency, that leads to improved application performance and support for increased number of applications.In virtualization-based Data Centers, the critical issue which attracted significant attention is the problem of VM placement. The VM placement problem uses resource requirements of VMs as input and based on the available capacity of the physical servers, VMs are placed on to servers sharing the resources in accordance with the Data Center Illustration of VM placement policies[67]. As the number of VMs and physical hosts increases in a Data Center, automation is required to do VM to server mapping.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Software defined networking and virtual machine placement in data centers

Kanagavelu¹

View full text Add to dashboard Cite

Application-Aware Virtual Machine Placement in Data Centers

Cited by 10 publications

References 11 publications

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

Network-Aware Virtual Machine Placement and Migration in Cloud Data Centers

Software defined networking and virtual machine placement in data centers

Contact Info

Product

Resources

About