Stable matching with ties for cloud-assisted smart TV services

Kim, Gyuyeong; Lee, Wonjun

doi:10.1109/icce.2014.6776132

Cited by 7 publications

(7 citation statements)

References 5 publications

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“…In order to put the VMP-SI model in the virtual machine selected by the fusion virtual machine proposed in this paper, the Cloudsim simulator is used. The latest version of Cloudsim provides many experimental data of energy consumption models of existing virtual machine migration strategies, which facilitates the comparison and research of energy-related virtual machine migration algorithms for cloud data centers by researchers [5]. All experiments are performed independently 1000 times, and then averaged [27][28].…”

Section: Experimental Results and Performance Analysis 41 Simulation Setupmentioning

confidence: 99%

“…According to the three phases steps of virtual machine migration, the better method in Cloudsim is to use the LRR strategy to detect the state of the physical host, combine the MMT strategy to complete the virtual machine selection, and then combine the CPP to complete the virtual machine placement. The above method is called a hybrid strategy, and its implementation results refer to [4][5]. The strategy proposed in this paper is mainly compared with the hybrid algorithm.…”

Section: Experimental Results and Performance Analysis 41 Simulation Setupmentioning

confidence: 99%

“…Virtual machine placement is essentially a classical packing problem (CPP), that is, placing a large number of candidate virtual machine VMs on a large number of physical nodes. There are also some literatures that call this problem stable matching or hospital bed allocation problem [5][6].…”

Section: Introductionmentioning

confidence: 99%

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A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

Zhang¹,

Yin²

2021

Journal on Internet of Things

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Cloud data centers face the largest energy consumption. In order to save energy consumption in cloud data centers, cloud service providers adopt a virtual machine migration strategy. In this paper, we propose an efficient virtual machine placement strategy (VMP-SI) based on virtual machine selection and integration. Our proposed VMP-SI strategy divides the migration process into three phases: physical host state detection, virtual machine selection and virtual machine placement. The local regression robust (LRR) algorithm and minimum migration time (MMT) policy are individual used in the first and section phase, respectively. Then we design a virtual machine migration strategy that integrates the process of virtual machine selection and placement, which can ensure a satisfactory utilization efficiency of the hardware resources of the active physical host. Experimental results show that our proposed method is better than the approach in Cloudsim under various performance metrics.

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Section: Experimental Results and Performance Analysis 41 Simulation Setupmentioning

confidence: 99%

Section: Experimental Results and Performance Analysis 41 Simulation Setupmentioning

confidence: 99%

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A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

Zhang¹,

Yin²

2021

Journal on Internet of Things

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“…VMs could rank PMs based on some properties such as transmission cost [93], migration time and cost [42] , processing capabilities [94] , and security [8] while PMs rank VMs based on their migration overhead [42] , CPU and resource utilization [15,94], and risk [8,61]. Kim and Lee [43] also considered the case where preferences are not necessarily a ranking and ties are allowed. The goal is often to minimize the overall dissatisfaction score which is defined as sum of ranks.…”

Section: Matchingmentioning

confidence: 99%

A Survey on the Use of Preferences for Virtual Machine Placement in Cloud Data Centers

Alashaikh¹,

Alanazi²,

Al-Fuqaha³

2019

Preprint

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With the rapid developments of virtualization techniques, cloud data centers have had enabled cost effective, flexible, and customizable deployments of applications in virtualized infrastructure. Virtual machine placement problem is a problem of paramount importance to the design of cloud data centers. It aims to assign each virtual machine to a server in the cloud environment. Typically, the problem involves complex relations and multiple design factors as well as local policies that govern the assignment decisions. It also involves different parties including cloud administrators and customers that we need to consider their preferences while opting for a solution. Thus, it is significant to not only return an optimized solution to the underlying placement problem but also a solution that reflects the given preferences of these parties. In this paper, we provide a detailed review on the role of preferences in the current literature of the virtual machine placement problem. We further discuss some challenges and identify possible research opportunities to better incorporate preferences within the problem.

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“…In their work, they formulated the VM co-scheduling problem as a cascade of a stable roommates problem and a stable matching problem. A recent work done by Kim et al in [4] suggested to formulate the VM migration process as a Hospital Residents problem. In their work, they considered VMs with equal requirement on resource.…”

Section: Introductionmentioning

confidence: 99%

A Stable Matching-Based Virtual Machine Allocation Mechanism for Cloud Data Centers

Wang

Fok

Cheng

et al. 2016

2016 IEEE World Congress on Services (SERVICES)

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Abstract-Virtualization is the enabling technology that makes resource provisioning in Cloud computing feasible. With virtualization, virtual machines (VMs) can be migrated across physical hosts to achieve better utilization of resource with a minimum impact on service quality. The VM allocation problem can be formulated as a stable matching problem. In this paper, we propose a VM allocation mechanism based on stable matching. A deferred acceptance procedure is adopted to handle conflicts among preferences of VMs and physical hosts. Unlike ordinary stable matching problems, both involving party groups in our matching process are having a mutual objective, that is to reduce the overall energy consumption of a Cloud data center while maintaining a high level of Quality of Service. The proposed mechanism is evaluated using CloudSim with real-world workload data. Simulation results show that Cloud data centers with the proposed mechanism can reduce energy consumption and avoid violations of ServiceLevel Agreement.

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Stable matching with ties for cloud-assisted smart TV services

Cited by 7 publications

References 5 publications

A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

A Virtual Machine Placement Strategy Based on Virtual Machine Selection and Integration

A Survey on the Use of Preferences for Virtual Machine Placement in Cloud Data Centers

A Stable Matching-Based Virtual Machine Allocation Mechanism for Cloud Data Centers

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