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.
The process of selecting which virtual machines should be located (i.e. executed) at each physical machine of a Datacenter is known as Virtual Machine Placement -VMP. This work proposes for the first time a multi-objective formulation of the VMP considering Service Level Agreement. A novel multiobjective memetic algorithm is also proposed to solve the formulated multi-objective problem. This proposal is validated comparing experimental results of the proposed algorithm with a brute force exhaustive search algorithm. Simulations prove the correctness of the proposed memetic algorithm and its scalability considering different experimental scenarios.
The process of selecting which virtual machines should be located (i.e. executed) at each physical machine of a datacenter is commonly known as Virtual Machine Placement (VMP). This work presents a general manyobjective optimization framework that is able to consider as many objective functions as needed when solving the VMP problem in a pure multi-objective context. As an example of utilization of the proposed framework, for the first time a formulation of the many-objective VMP problem (MaVMP) is proposed, considering the simultaneous optimization of the following five objective functions: (1) power consumption, (2) network traffic, (3) economical revenue, (4) quality of service and (5) network load balancing. To solve the formulated many-objective VMP problem, an interactive memetic algorithm is proposed. Simulations prove the correctness of the proposed algorithm and its effectiveness converging to a treatable number of solutions in different experimental scenarios.
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