Virtual Machine Placement Literature Review

Cloud Computing Datacenters host millions of virtual machines (VMs) on real world scenarios. In this context, Virtual Machine Placement (VMP) is one of the most challenging problems in cloud infrastructure management, considering also the large number of possible optimization criteria and different formulations that could be studied. VMP literature include relevant topics such as energy-efficiency, Service Level Agreements (SLA), cloud service markets, Quality of Service (QoS) and carbon dioxide emissions, all of them with high economical and ecological impact. This work presents an extensive up-to-date review of the most relevant VMP literature in order to identify research opportunities. I. BACKGROUND AND MOTIVATION The process of selecting which virtual machines (VMs) should be located (i.e. executed) at each physical machine (PM) of a datacenter is known as Virtual Machine Placement (VMP). The VMP problem has been extensively studied in cloud computing literature and several surveys have already been presented. Existing surveys focus on specific issues such as: (1) energy-efficient techniques applied to the problem [5], [70], (2) particular architectures where the VMP problem is applied, specifically federated clouds [27] and (3) methods for comparing performance of placement algorithms in large ondemand clouds [63]. Beloglazov et al. presented in [5] a survey of energy-aware resource allocation policies and scheduling algorithms considering QoS. The following open challenges were identified considering energy-aware management of cloud computing datacenters: (1) development of fast energy-efficient algorithms for the VMP, considering multiple resources for largescale systems with the ability to predict workload peaks to prevent performance degradation, (2) energy-aware optimization of virtual network topologies between VMs for optimal placement in order to reduce network traffic and thus energy consumed by the network infrastructure, (3) development of new thermal management algorithms to appropriately control temperature and energy consumption, (4) development of workload-aware resource allocation algorithms, considering that current approaches assume a uniform workload, and (5) decentralization and distributed approaches to provide scalability and fault-tolerance to the VMP problem resolution. Salimian et al. presented a review of different selection and placement algorithms for energy-efficient management of cloud computing datacenters [70]. Approaches for virtual and physical resources modeling, applied techniques and future work were identified for each studied article. Most relevant future work include: (1) investigation of VMP for multi-core architectures considering multiple resources, (2) consideration of dynamic thresholds for QoS and (3) development of intelligent schemes according to workload and considering live migration. Gahlawat et al. proposed in [27] a brief survey of the main cloud federation architectures and approaches considered for VMP problem formulation in this particular scenario. It is important to remember that cloud federation is the practice of voluntarily interconnecting cloud infrastructures of different Cloud Service Providers (CSPs), mostly to respond to workload peaks. Finally, Mills et al. presented in [63] an objective method to compare performance of placement algorithms in large ondemand clouds, where 18 different algorithms for VMP were compared considering 39 variables such as: reallocation rate, user request rate, allocation rate and disk space utilization, just for cite a few. The above mentioned surveys and research articles focused into specific issues related to the VMP problem. To the best of the author’s knowledge, there is not existing research work that presents a general and extensive study of a large part of the VMP literature. This work presents an extensive up-todate review of the most relevant VMP literature in order to identify research opportunities on this important and promising research area. II. REVIEWED LITERATURE A selection process of current research work was defined and performed in order to study a large part of the most relevant VMP literature for this survey. This section presents a detailed description of the literature selection process which is summarized in Figure 1.