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Cloud computing consists of physical data centers each of which including hundreds or thousands of computers. A key enabler technology is virtualization. The Virtualization allows us to separate virtual machines in a way that each of these so-called virtualized machines can be configured with a number of hosts according to the type of application of the user. It is also possible to dynamically alter the allocated resources of a virtual machine. One of the most important challenges in terms of cloud computing is to maintain an optimized load balance in cloud environment on servers because this issue is critical for energy consumption. In this paper, we propose a hybrid method for reduction of... 

With the increasing popularity of cloud computing services, the more number of cloud data centers are constructed over the globe. This makes the power consumption of cloud data center elements as a big challenge. Hereby, several software and hardware approaches have been proposed to handle this issue. However, this problem has not been optimally solved yet. In this paper, we propose an online cloud resource management with live migration of virtual machines (VMs) to reduce power consumption. To do so, a prediction-based and power-aware virtual machine allocation algorithm is proposed. Also, we present a three-tier framework for energy-efficient resource management in cloud data centers.... 

There are several physical data centers in cloud environment with hundreds or thousands of computers. Virtualization is the key technology to make cloud computing feasible. It separates virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts according to the type of user application. It is also possible to dynamically alter the allocated resources of a virtual machine. Different methods of energy saving in data centers can be divided into three general categories: 1) methods based on load balancing of resources; 2) using hardware facilities for scheduling; 3) considering thermal characteristics of the environment. This paper focuses... 

Energy usage of data centers is a challenging and complex issue because computing applications and data are growing so quickly that increasingly larger servers and disks are needed to process them fast enough within the required time period. In the past few years, many approaches to virtual machine placement have been proposed. This study proposes a new approach for virtual machine allocation to physical hosts. Either minimizes the physical hosts and avoids the SLA violation. The proposed method in comparison to the other algorithms achieves better results. Copyright © 2019 Institute of Advanced Engineering and Science. All rights reserved  

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved  

Cloud computing is a new framework, which is facing a numerous type of challenges including resource management and energy consumption of data centers. One of the most important duties of cloud service providers is to manage resources and schedule tasks for reducing energy consumption in data centers. In this paper, fuzzy logic is used for finding most adequate DC, improved DVFS algorithm is used for selecting ideal host and developed version of EDF-VD algorithm is utilized for Task scheduling and load balance in cloud computing. Our approach improvement to the current methods including EEVS, DVFS, Homogeneous, MBFD and EEVS-N. © 2019-IOS Press and the authors. All rights reserved  

Efficiency in cloud servers’ power consumption is of paramount importance. Power efficiency makes the reduction in greenhouse gases establishing the concept of green computing. One of the beneficial ways is to apply power-aware methods to decide where to allocate virtual machines (VMs) in data center physical resources. Virtualization is utilized as a promising technology for power-aware VM allocation methods. Since the VM allocation is an NP-complete problem, we use of evolutionary algorithms to solve it. This paper presents an effective micro-genetic algorithm in order to choose suitable destinations between physical hosts for VMs. Our evaluations in simulation environment show that...