325 research outputs found
Allocation of Virtual Machines in Cloud Data Centers - A Survey of Problem Models and Optimization Algorithms
Data centers in public, private, and hybrid cloud settings make it possible to provision virtual machines
(VMs) with unprecedented flexibility. However, purchasing, operating, and maintaining the underlying physical
resources incurs significant monetary costs and also environmental impact. Therefore, cloud providers must
optimize the usage of physical resources by a careful allocation of VMs to hosts, continuously balancing between
the conflicting requirements on performance and operational costs. In recent years, several algorithms have been
proposed for this important optimization problem. Unfortunately, the proposed approaches are hardly comparable
because of subtle differences in the used problem models. This paper surveys the used problem formulations and
optimization algorithms, highlighting their strengths and limitations, also pointing out the areas that need further
research in the future
Modeling the virtual machine allocation problem
Finding the right allocation of virtual machines (VM) in cloud data centers is one of the key optimization
problems in cloud computing. Accordingly, many algorithms have been proposed for the problem. However,
lacking a single, generally accepted formulation of the VM allocation problem, there are many subtle differences
in the problem formulations that these algorithms address; moreover, in several cases, the exact problem formu-
lation is not even defined explicitly. Hence in this paper, we present a comprehensive generic model of the VM
allocation problem. We also show how the often-investigated problem variants fit into this general model
A review on various optimization techniques of resource provisioning in cloud computing
Cloud computing is the provision of IT resources (IaaS) on-demand using a pay as you go model over the internet.It is a broad and deep platform that helps customers builds sophisticated, scalable applications. To get the full benefits, research on a wide range of topics is needed. While resource over-provisioning can cost users more than necessary, resource under provisioning hurts the application performance. The cost effectiveness of cloud computing highly depends on how well the customer can optimize the cost of renting resources (VMs) from cloud providers. The issue of resource provisioning optimization from cloud-consumer potential is a complicated optimization issue, which includes much uncertainty parameters. There is a much research avenue available for solving this problem as it is in the real-world. Here, in this paper we provide details about various optimization techniques for resource provisioning
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