A clustered virtual machine allocation strategy based on a sleep-mode with wake-up threshold in a cloud environment

2019 ◽  
Vol 293 (1) ◽  
pp. 193-212 ◽  
Author(s):  
Shunfu Jin ◽  
Xiuchen Qie ◽  
Wenjuan Zhao ◽  
Wuyi Yue ◽  
Yutaka Takahashi
Keyword(s):  
Virtual Machine ◽  
Sleep Mode ◽  
Cloud Environment ◽  
Allocation Strategy ◽  
Machine Allocation ◽  
Virtual Machine Allocation

scholarly journals Improved Virtual Machine Allocation Strategy using Particle Swarm Optimization Algorithm

2018 ◽  
Vol 7 (2.7) ◽  
pp. 813
Author(s):  
B Thirumala Rao ◽  
K Nandavardhini ◽  
K Navya ◽  
G Krishna Venkata Sunil
Keyword(s):  
Virtual Machine ◽  
Virtual Machines ◽  
Particle Swarm Optimization Algorithm ◽  
Critical Issue ◽  
Allocation Strategy ◽  
Swarm Optimization ◽  
Machine Allocation ◽  
Virtual Machine Allocation ◽  
Cloud Condition ◽  
Cross System

Virtual machine position (VMP) is a critical issue in choosing most appropriate arrangement of physical machines (PMs) for an arrangement of virtual machines (VMs) in distributed computing condition. These days information concentrated applications for handling huge information are being facilitated in the cloud. Since the cloud condition gives virtualized assets to calculation, and information concentrated applications require correspondence between the registering hubs, the situation of Virtual Machines (VMs) and area of information influence the general calculation time. The essential target is to decrease cross system activity and transmission capacity use, by setting required number of VMs and information in Physical Machines (PMs) which are physically nearer. This paper exhibits and assesses by a meta-heuristic calculation in view of Parallel Computing and Optimization (PCO) which select an arrangement of adjoining PMs for setting information and VMs . In the wake of choosing the PMs, the information are duplicated to the capacity gadgets of the PMs and the required number of VMs are begun on the PMs based on their VM allotment limits. Recreation comes about demonstrate that this determination diminishes the whole of separations amongst VMs and henceforth lessens the activity fruition time.

scholarly journals Performance Evaluation and Social Optimization of an Energy-Saving Virtual Machine Allocation Scheme Within a Cloud Environment

2019 ◽  
Vol 8 (4) ◽  
pp. 561-580
Author(s):  
Xiushuang Wang ◽  
Jing Zhu ◽  
Shunfu Jin ◽  
Wuyi Yue ◽  
Yutaka Takahashi
Keyword(s):  
Energy Saving ◽  
Virtual Machine ◽  
Arrival Rate ◽  
Adaptive Genetic Algorithm ◽  
Cloud Environment ◽  
Allocation Scheme ◽  
Network Resource ◽  
Pricing Policy ◽  
Machine Allocation ◽  
Virtual Machine Allocation

AbstractAchieving greener cloud computing is non-negligible for the open-source cloud platform. In this paper, we propose a novel virtual machine allocation scheme with a sleep-delay and establish a corresponding mathematical model. Taking into account the number of tasks and the state of the physical machine, we construct a two-dimensional Markov chain and derive the average latency of tasks and the energy-saving degree of the system in the steady state. Moreover, we provide numerical experiments to show the effectiveness of the proposed scheme. Furthermore, we study the Nash equilibrium behavior and the socially optimal behavior of tasks and carry out an improved adaptive genetic algorithm to obtain the socially optimal arrival rate of tasks. Finally, we present a pricing policy for tasks to maximize the social profit when managing the network resource within the cloud environment.

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