Dynamic Virtual Machine Placement in Cloud Computing

Paul, Arnab; Sahoo, Bibhudatta

doi:10.4018/978-1-5225-1721-4.ch006

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…E.g., L. Guo et al [17] used a cooperative game model to guide VM consolidation with load and energy constraints, which is tested in a homogeneous cloud environment. Paul [18] proposed an uncooperative game-theoretic algorithm for dynamic VM consolidation problem in cloud computing. Xue et al [19] used a coalitional game model to schedule the tasks in cloud.…”

Section: Game-theoretic Scheduling In Cloudmentioning

confidence: 99%

A Workload-Aware VM Consolidation Method Based on Coalitional Game for Energy-Saving in Cloud

et al. 2019

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Virtual Machine (VM) consolidation technique plays an important role in energy management and load-balancing of cloud computing systems. Dynamic VM consolidation is a promising consolidation approach in this direction, which aims at using least active physical machines (PMs) through appropriately migrating VMs to reduce resource consumption. The resulting optimization problem is well-acknowledged to be NP-hard optimization problems. In this paper, we propose a novel merge-and-split-based coalitional game-theoretic approach for VM consolidation in heterogeneous clouds. The proposed approach first partitions PMs into different groups based on their workload levels, then employs a coalitional-game-based VM consolidation algorithm (CGMS) in choosing members from such groups to form effective coalitions, performs VM migrations among the coalition members to maximize the payoff of every coalition, and finally keeps PMs running in a high energy-efficiency state. The simulation results based on three scenarios clearly suggest that our proposed approach outperforms traditional ones in terms of energy-saving, and also achieve a fair level of load balance.

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Section: Game-theoretic Scheduling In Cloudmentioning

confidence: 99%

A Workload-Aware VM Consolidation Method Based on Coalitional Game for Energy-Saving in Cloud

et al. 2019

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“…Physical Machine: Physical machine is a set of hardware like CPU, RAM, I/O which are request for applications. 6. Virtualization: Virtualization is basically process of making a virtual image of cloud resources such as server, desktop, operating system, storage devices or network [4].…”

Section: Client (End User)mentioning

confidence: 99%

“…Virtual Machine (VM) requests should be first distributed optimally over datacenters. The requests in each datacenter are then distributed over physical machines if required resources are available [6]. Resource allocation problem is formulated as bin packing Problem.…”

Section: Resource Allocation In Cloudmentioning

confidence: 99%

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A Review: Resource Allocation Problem in Cloud Environment

Pandharpatte¹

2017

IJET

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Abstract-Cloud computing is the process of providing and managing computing resources such as hardware and software over the Internet as pay-as-you-go. Cloud Service Provider and User are two main players in cloud. On one hand, cloud provider carries number of computing resources in their large datacenters and rent resources out to users on pay-as-you-go basis. On the other hand, there are large numbers of users who have applications with changing loads and request required resources from providers to run their applications slickly. Typically, the goal of providers is to generate as much revenue as possible with minimum investment and proper resource utilization. On the other hand, users want their jobs done at minimal expense. In the Cloud computing resources need to be allocated and scheduled in such a way that providers achieve their objectives and users meet their applications requirements with minimum expenditure. We call this as a cloud resource allocation problem. Resource allocation is traditionally looked upon as an optimization problem hence resource allocation is NP-Hard; limited resources are available and allocate these resources to competitive events/activities such a way that both parties will achieve their goals. 1. Client (End User): Clients are the devices that the end user interact with to manage their information on the client. 2. Provider: Cloud Service provider is an owner of cloud infrastructure who provides services to requester via internet on pay-as-you-basis. 3. Datacenter: A datacenter is a set of physical resources such as CPU, memory, storage, and so on. 4. Virtual Machine: Simulation of a Physical Machine in the form of Software is known as a virtual machine. 5. Physical Machine: Physical machine is a set of hardware like CPU, RAM, I/O which are request for applications.

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