Service-Aware Cloud-to-Cloud Migration of Multiple Virtual Machines

Narantuya, Jargalsaikhan; Zang, Hannie; Lim, Hyuk

doi:10.1109/access.2018.2882651

Cited by 14 publications

(3 citation statements)

References 13 publications

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“…Since all of the data center resources are controlled by software-defined technologies, the infrastructure can be dynamically configured, and the necessary data for the proposed strategy can be easily obtained. Moreover, SDC enables VMs to be moved between different PMs with the support of a VM migration technique [43].…”

Section: System Descriptionmentioning

confidence: 99%

Dependency Analysis based Approach for Virtual Machine Placement in Software-Defined Data Center

Narantuya

Bae

et al. 2019

Applied Sciences

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In data centers, cloud-based services are usually deployed among multiple virtual machines (VMs), and these VMs have data traffic dependencies on each other. However, traffic dependency between VMs has not been fully considered when the services running in the data center are expanded by creating additional VMs. If highly dependent VMs are placed in different physical machines (PMs), the data traffic increases in the underlying physical network of the data center. To reduce the amount of data traffic in the underlying network and improve the service performance, we propose a traffic-dependency-based strategy for VM placement in software-defined data center (SDDC). The traffic dependencies between the VMs are analyzed by principal component analysis, and highly dependent VMs are grouped by gravity-based clustering. Each group of highly dependent VMs is placed within an appropriate PM based on the Hungarian matching method. This strategy of dependency-based VM placement facilitates reducing data traffic volume of the data center, since the highly dependent VMs are placed within the same PM. The results of the performance evaluation in SDDC testbed indicate that the proposed VM placement method efficiently reduces the amount of data traffic in the underlying network and improves the data center performance.

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Section: System Descriptionmentioning

confidence: 99%

Dependency Analysis based Approach for Virtual Machine Placement in Software-Defined Data Center

Narantuya

Bae

et al. 2019

Applied Sciences

Self Cite

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“…We would like to thank Professor Olivier Festor for his very helpful comments and advices on the submitted article. 1 Satisfiability Modulo Theories recent advances on virtualization techniques [2], allowing to transfer the resource(s) of a cloud composite service from a given provider (or a given infrastructure) to another provider (or infrastructure) [3]. This process is often motivated by performance and cost objectives with regard to the cloud properties, such as high scalability, rapid elasticity, resource pooling and on-demand self-service [4].…”

Section: Introductionmentioning

confidence: 99%

An Automated SMT-based Security Framework for Supporting Migrations in Cloud Composite Services

Oulaaffart

Badonnel

Bianco

2022

NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium

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The growing maturity of orchestration languages is contributing to the elaboration of cloud composite services, whose resources may be deployed over different distributed infrastructures. These composite services are subject to changes over time, that are typically required to support cloud properties, such as scalability and rapid elasticity. In particular, the migration of their elementary resources may be triggered by performance constraints. However, changes induced by this migration may introduce vulnerabilities that may compromise the resources, or even the whole cloud service. In that context, we propose an automated SMT 1 -based security framework for supporting the migration of resources in cloud composite services, and preventing the occurrence of new configuration vulnerabilities. We formalize the underlying security automation based on SMT solving, in order to assess the migrated resources and select adequate counter-measures, considering both endogenous and exogenous security mechanisms. We then evaluate its benefits and limits through large series of experiments based on a proof-ofconcept prototype implemented over the CVC4 commonly-used open-source solver. These experiments show a minimal overhead with regular operating systems deployed in cloud environments.

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“…is 45% (Narantuya, et al, 2018;Zakarya, 2018). Therefore, the factors mentioned above are very important for identifying energy-based resource allocation at the cloud data center to make a green data center (Kansal & Chana, 2016;Sharma & Reddy, 2016).…”

mentioning

confidence: 99%

Cat-Squirrel Optimization Algorithm for VM Migration in a Cloud Computing Platform

C.¹,

Sivakumar

2022

International Journal on Semantic Web and Information Systems

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This paper introduces an approach for the VM migration based on optimization algorithm, named CS in cloud. The provider to be selected is carried out with the usage of multiple constraints, like delay, bandwidth, cost, and load. Subsequently, the effective searching criteria are computed for finding the optimal service on the basis of fitness constraints. The searching criteria are formulated as optimization problems, which are tackled using CS. The proposed CS is designed by integrating CSO with the SSA such that the fitness function is evaluated for the optimal VM migration by considering several parameters, such as delay, cost, bandwidth, and load. Thus, the cloud manager will perform the migration of VM in cloud based on proposed CS-based VM migration approach. The performance of the CS-based VM migration is evaluated in terms of delay, cost, and load. The proposed CS-based VM migration method achieves the minimal delay of 0.146, minimal cost of 0.052, and the minimal load of 0.182.

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Service-Aware Cloud-to-Cloud Migration of Multiple Virtual Machines

Cited by 14 publications

References 13 publications

Dependency Analysis based Approach for Virtual Machine Placement in Software-Defined Data Center

Dependency Analysis based Approach for Virtual Machine Placement in Software-Defined Data Center

An Automated SMT-based Security Framework for Supporting Migrations in Cloud Composite Services

Cat-Squirrel Optimization Algorithm for VM Migration in a Cloud Computing Platform

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