CloudTB: A quick and reliable testbed for virtual machine based cloud computing systems

2015 ◽  
Author(s):  
Yushuai Shi ◽  
Deqing Zou ◽  
Weizhong Qiang ◽  
Xiaofei Liao ◽  
Hai Jin
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Computing Systems

Burstiness-aware virtual machine placement in cloud computing systems

2019 ◽  
Vol 76 (1) ◽  
pp. 362-387 ◽  
Author(s):  
Somayeh Rahmani ◽  
Vahid Khajehvand ◽  
Mohsen Torabian
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machine Placement ◽  
Computing Systems

scholarly journals An efficient algorithm for monitoring virtual machines in clouds

2019 ◽  
Vol 8 (2) ◽  
pp. 699-705
Author(s):  
Sultan Alshamrani
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Efficient Algorithm ◽  
Virtual Machines ◽  
End Users ◽  
Round Robin ◽  
Computing Systems ◽  
Cloud Systems ◽  
Increasing Demand ◽  
Set Up

Cloud computing systems consist of a pool of Virtual Machines (VMs), which are installed physically on the provider's set up. The main aim of the VMs is to offer the service to the end users. With the current increasing demand for the cloud VMs, there is always a huge requirement to secure the cloud systems. To keep these cloud systems secured, they need a continuous and a proper monitoring. For the purpose of monitoring, several algorithms are available with FVMs. FVM is a forensic virtual machine which monitors the threats among the VMs. Our formulated algorithm runs on FVM. In this paper, we formulate the Random-Start-Round-Robin algorithm for monitoring inside FVM.

Application of virtual machine consolidation in cloud computing systems

2021 ◽  
Vol 30 ◽  
pp. 100524
Author(s):  
Rahmat Zolfaghari ◽  
Amir Sahafi ◽  
Amir Masoud Rahmani ◽  
Reza Rezaei
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Computing Systems ◽  
Virtual Machine Consolidation

A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

2017 ◽  
Vol 7 (9) ◽  
pp. 30 ◽  
Author(s):  
Ramandeep Kaur
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Heuristic Algorithms ◽  
Hybrid Approach ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Bee Colony ◽  
Effective Manner ◽  
Effective Performance

A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

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