An Efficient Technique for Virtual Machine Clustering and Communications Using Task-Based Scheduling in Cloud Computing

Cloud computing models use virtual machine (VM) clusters for protecting resources from failure with backup capability. Cloud user tasks are scheduled by selecting suitable resources for executing the task in the VM cluster. Existing VM clustering processes suffer from issues like preconfiguration, downtime, complex backup process, and disaster management. VM infrastructure provides the high availability resources with dynamic and on-demand configuration. The proposed methodology supports VM clustering process to place and allocate VM based on the requesting task size with bandwidth level to enhance the efficiency and availability. The proposed clustering process is classified as preclustering and postclustering based on the migration. Task and bandwidth classification process classifies tasks with adequate bandwidth for execution in a VM cluster. The mapping of bandwidth to VM is done based on the availability of the VM in the cluster. The VM clustering process uses different performance parameters like lifetime of VM, utilization of VM, bucket size, and task execution time. The main objective of the proposed VM clustering is that it maps the task with suitable VM with bandwidth for achieving high availability and reliability. It reduces task execution and allocated time when compared to existing algorithms.

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From high-availability to collapse: quantitative analysis of “Cloud-Droplet-Freezing” attack threats to virtual machine migration in cloud computing

Cluster Computing ◽

10.1007/s10586-014-0388-6 ◽

2014 ◽

Vol 17 (4) ◽

pp. 1369-1381 ◽

Cited By ~ 9

Author(s):

Yichuan Wang ◽

Jianfeng Ma ◽

Di Lu ◽

Xiang Lu ◽

Liumei Zhang

Keyword(s):

Cloud Computing ◽

Quantitative Analysis ◽

Virtual Machine ◽

Cloud Droplet ◽

High Availability ◽

Virtual Machine Migration

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Performance Comparison between VM Based Webserver and Docker Container Webserver

Asian Journal of Computer Science and Technology ◽

10.51983/ajcst-2019.8.s2.2030 ◽

2019 ◽

Vol 8 (S2) ◽

pp. 28-30

Author(s):

A. Anand ◽

A. Nisha Jebaseeli

Keyword(s):

Cloud Computing ◽

Virtual Machine ◽

Performance Metrics ◽

Performance Comparison ◽

Light Weight ◽

Performance Parameters ◽

It Services ◽

Network Bandwidth ◽

On Demand ◽

Processing Resources

Cloud computing is a type of Internet-based computing that provides shared computer processing resources, services and data to computers on demand. It offers an innovative business model for organizations to adopt IT services at a reduced cost with increased reliability and scalability. Virtualisation is one of backbone technology of cloud computing. But today, container based technology especially Docker offering better performance than Virtual Machine. It is famous for its light weight operation and better scaling. But still it is lagging in Disk I/O and network bandwidth intensive applications. So it is important to analyse and compare various performance parameters of VMs and Docker Images before implementation. Main Parameters will be CPU, Memory, Disk Utilization and Network Bandwidth. In this research paper, we compare performance metrics between Webserver deployed in Virtual machine and Docker webserver.

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A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i9.407 ◽

2017 ◽

Vol 7 (9) ◽

pp. 30 ◽

Cited By ~ 1

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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The virtual machine secure migration model in cloud computing

Advances in Computer Science and Technology ◽

10.2495/iccst140671 ◽

2014 ◽

Author(s):

Z. T. Ma ◽

G. Yang ◽

H. N. Gong

Keyword(s):

Cloud Computing ◽

Virtual Machine ◽

Migration Model

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Clustering Server Pada Cloud Computing Berbasis Proxmox VE Menggunakan Metode High Availability

JOINTECS (Journal of Information Technology and Computer Science) ◽

10.31328/jointecs.v3i1.498 ◽

2018 ◽

Vol 3 (1) ◽

Author(s):

Linda Apriliana ◽

Ucuk Darusala Darusalam ◽

Novi Dian Nathasia

Keyword(s):

Cloud Computing ◽

File System ◽

High Availability ◽

Client Server ◽

Network File System

Layanan dan data teknologi Cloud Computing tersimpan pada server, hal ini menjadikan faktor pentingnya server sebagai pendukung ketersediaan layanan. Semakin banyak pengguna yang mengakses layanan tersebut akan mengakibatkan beban kinerja mesin server menjadi lebih berat dan kurang optimal, karena layanan harus bekerja menyediakan data terus-menerus yang dapat diakses kapanpun oleh penggunanya melalui jaringan terkoneksi. Perangkat keras server memiliki masa performa kinerja. Hal serupa dengan perangkat lunak yang dapat mengalami crash. Dengan fungsi server yang memberikan layanan kepada client, server dituntut untuk memiliki tingkat availability yang tinggi. Hal tersebut memungkinkan mesin server mengalami down. Server juga harus dimatikan untuk keperluan pemeliharaan. Penelitian bertujuan ini membangun Clustering Server yang dapat bekerja bersama yang seolah merupakan sistem tunggal diatas lingkungan virtual. Hal ini merupakan solusi untuk mengatasi permasalahan tersebut. Pada penelitian ini penulis menggunakan server virtualisasi proxmox, FreeNAS sebagai server NAS dan DRBD untuk pendukung ketersediaan layanan tinggi dalam lingkup HA, sinkronisasi data dalam High Availability (HA) yang dapat melakukan mirroring sistem kemesin lain. Dengan diterapkannya metode HA dan sinkronasi DRBD serta penggunaan NFS (Network File System) pada sistem cluster didapatkan hasil rata-rata waktu migrasi sebesar 9.7(s) pada node1 menuju node2, 3.7(s) node2 menuju node3, dan 3(s) pada node3 menuju node1. Didaptkan juga waktu downtime yang lebih sedikit yaitu sebesar 0.58 ms pada node1, 0.02 ms pada node2, dan 0.02 ms pada node3.

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Distance Aware VM allocation process to minimize energy consumption in cloud computing

Recent Patents on Computer Science ◽

10.2174/2213275912666191023143709 ◽

2019 ◽

Vol 12 ◽

Author(s):

Gurpreet Singh ◽

Manish Mahajan ◽

Rajni Mohana

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Energy Consumption ◽

Virtual Machine ◽

Virtual Machines ◽

Research Work ◽

Service Level Agreement ◽

Service Level ◽

Physical Machine ◽

Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

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