VM Placement Strategies for Cloud Scenarios

Calcavecchia, Nicolò Maria; Biran, Ofer; Hadad, Erez; Moatti, Yosef

doi:10.1109/cloud.2012.113

Cited by 99 publications

(49 citation statements)

References 13 publications

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“…The weight w assigned to each resource represents the impact of those resources in total migration overhead, considering that network (w = 0.8) and storage (w = 0.6) resources have more impact than Random Access Memory (RAM) (w = 0.4) or CPU (w = 0.1). Another approach for a live migration network overhead optimization in VMP is presented in [9], where live migrations are limited to a maximum number, modeled as a constraint of the problem.…”

Section: B Network Traffic Minimizationmentioning

confidence: 99%

A Virtual Machine Placement Taxonomy

Pires¹,

Barán²

2015

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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Cloud computing datacenters dynamically provide millions of virtual machines (VMs) in actual cloud markets. In this context, Virtual Machine Placement (VMP) is one of the most challenging problems in cloud infrastructure management, considering the large number of possible optimization criteria and different formulations that could be studied. VMP literature include relevant research topics such as energy efficiency, Service Level Agreement (SLA), Quality of Service (QoS), cloud service pricing schemes and carbon dioxide emissions; all of them with high economical and ecological impact. This work classifies an extensive up-to-date survey of the most relevant VMP literature proposing a novel taxonomy in order to identify research opportunities and define a general vision on this research area.

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Section: B Network Traffic Minimizationmentioning

confidence: 99%

A Virtual Machine Placement Taxonomy

Pires¹,

Barán²

2015

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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“…Specifically, application-level monitoring of VMs must be adopted to detect when the expected performance of the VMs drops below a given threshold. In this case, in order to mitigate the hot-spots, additional resources are either added locally, or if the total resource usage of the host running the VM exceeds a predefined threshold, a decision-making process is enabled to migrate the VM to another HM [23,24].…”

Section: Background and Related Workmentioning

confidence: 99%

A coral-reefs and Game Theory-based approach for optimizing elastic cloud resource allocation

Ficco

Esposito

Palmieri

et al. 2018

Future Generation Computer Systems

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“…In general, the OSP problem is well known as VM placement and its previous approaches focus on CPU, memory and disk I/O resource saving [3][2] [5], in order to improve the utilization ratio of infrastructures [5] and save energy [4][12] [9]. Most works in these researches formulate the VM placement problem as an optimization problem, such as bin packing problem.…”

Section: Related Workmentioning

confidence: 99%

Guarantee high reliability and effectiveness for softwares in internetware

Zhang

Chen

et al. 2014

Proceedings of the 6th Asia-Pacific Symposium on Internetware on Internetware

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Internetware challenges distributed systems in aspects from operating platforms, programming models, to engineering approaches, etc. Cloud computing based on virtualization is now a popular paradigm which can meet the dynamic resource allocation requirements of Internetware. Software entities dispersed on distributed nodes over the Internet, now are evolving into self-contained, autonomous software services. These software entities which are often deployed on virtual machines (VMs), are coordinated dynamically to achieve flexible design objectives. To improve the utilization of infrastructure resource, VMs processing components of a software should be consolidated to fewer physical machines (PMs). However, as the increasing trends of communication-intensive softwares, data traffic among VMs should be considered as well. And for the sake of safety and QoS (Quality of Service), certain VMs (e.g. backup nodes) are mutually-exclusive which means some VMs require to be placed on different PMs. In this paper, we investigate the online software placement problem with the target to minimize the network traffic cost, while taking into account the mutually-exclusiveness of VMs. We provide a formal problem description and its NP-hardness analysis. The proposed algorithm places the VMs that have heavy traffic on the same PM, while isolating the mutually-exclusive VMs simultaneously, which can guarantee high effectiveness and reliability for softwares in Internetware, respectively. The simulations show our algorithm reduces the traffic cost by 29% compared against the existing approaches.

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VM Placement Strategies for Cloud Scenarios

Cited by 99 publications

References 13 publications

A Virtual Machine Placement Taxonomy

A Virtual Machine Placement Taxonomy

A coral-reefs and Game Theory-based approach for optimizing elastic cloud resource allocation

Guarantee high reliability and effectiveness for softwares in internetware

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