scholarly journals Optimize Elasticity in Cloud Computing using Container Based Virtualization

2019 ◽  
Author(s):  
Muhammad Amir Shahzad ◽  
Muhammad Sohaib Aslam ◽  
Waseem Sajjad ◽  
Muhammad Imran
Keyword(s):  
Cloud Computing ◽  
Response Time ◽  
Virtual Machine ◽  
Cloud Provider ◽  
Great Efficiency ◽  
Heavy Load ◽  
User Request ◽  
Long Time ◽  
Key Features ◽  
Short Time

Cloud computing emphasis on using and underlying infrastructure in a much efficient way. That’s why it is gaining immense importance in today’s industry. Like every other field, cloud computing also has some key feature for estimating the standard of working of every cloud provider. Elasticity is one of these key features. The term elasticity in cloud computing is directly related to response time (a server takes towards user request during resource providing and de-providing. With increase in demand and a huge shift of industry towards cloud, the problem of handling user requests also arisen. For a long time, the concept of virtualization held industry with all its merits and demerits to handle multiple requests over cloud. Biggest disadvantage of virtualization shown heavy load on underlying kernel or server but from past some decades an alternative technology emerges and get popular in a short time due to great efficiency known as containerization. In this paper we will discuss about elasticity in cloud, working of containers to see how it can help to improve elasticity in cloud for this will using some tools for analyzing two technologies i.e. virtualization and containerization. We will observe whether containers show less response time than virtual machine. If yes that’s mean elasticity can be improved in cloud on larger scale which may improve cloud efficiency to a large extent and will make cloud more eye catching.

Efficient task scheduling on virtual machine in cloud computing environment

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahfooz Alam ◽  
Mahak ◽  
Raza Abbas Haidri ◽  
Dileep Kumar Yadav
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Virtual Machine ◽  
Task Allocation ◽  
Completion Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Content Type ◽  
Minimum Completion Time

Purpose Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization. Design/methodology/approach Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing. Findings To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time. Originality/value The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

scholarly journals Proses Migrasi Cloud Computing Dari Lingkungan Amazon Ec2 Ke Vmware

2019 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Jauharul Mafakhiri
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Service Level Agreement ◽  
Service Level ◽  
Cloud Provider ◽  
Test Case ◽  
Infrastructure As A Service ◽  
Amazon Ec2 ◽  
Lock In

Intisari— Permasalahan pada penelitian ini adalah mengenai pengujian virtual machine di tingkat fungsionalitas aplikasi pada lingkungan komputasi awan di antara dua cloud provider IaaS (Infrastructure as a Service). Tujuan dari pengujian fungsionalitas ini adalah untuk mengetahui tingkat interoperabilitas aplikasi dalam sistem virtual machine yang berpindah dari sebuah cloud provider ke cloud provider lain, yaitu migrasi dari Amazon EC2 ke VMWARE. Peneliti memiliki ketertarikan mengenai pengujian migrasi ini sebab perkembangan Internet menjadi semakin pesat, dan diiringi dengan meningkatnya jumlah aplikasi yang memanfaatkan teknologi komputasi awan itu, sementara kemampuan proses bisnis suatu aplikasi semakin bertambah, fitur layanan yang ditawarkan para pihak cloud provider menjadi semakin baik (dari sisi harga menjadi lebih murah, performansi sistem menjadi lebih tinggi, sistem menjadi lebih handal, pemanfaatan kecanggihan teknologi security terbaru, maupun Service Level Agreement (SLA) menjadi lebih baik), maka memungkinkan untuk berpindah layanan ke cloud provider lain, namun di sisi praktik sering terjadi kegagalan fungsionalitas aplikasi dalam proses migrasi ke sistem cloud yang lain, yang antara lain disebabkan oleh masalah ketergantungan terhadap penyedia layanan komputasi awan (vendor lock-in). Masalah ketergantungan ini muncul disebabkan oleh jumlah cloud provider semakin bertanbah banyak dan mempunyai standar tersendiri dalam pembangunan sistemnya, sehingga dapat mengakibatkan kemampuan migrasi antar cloud itu dapat memiliki keterbatasan untuk hal-hal tertentu. Dengan 28 test case pengujian atas fitur-fitur pada aplikasi website ujian online yang diuji pada penelitian ini, diperoleh hasil tingkat interoperabilitas migrasi dari Amazon EC2 ke VMWARE memiliki nilai sebesar 46.43%. Kata kunci— pengujian, fungsionalitas, komputasi, awan, migrasi, interoperabilitas.

A survey on virtualization techniques in Mobile edge computing

2021 ◽  
pp. 455-468
Author(s):  
Durga Chouhan ◽  
Nilima Gautam ◽  
Gaurav Purohit ◽  
Rajesh Bhdada
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Large Scale ◽  
Cloud Infrastructure ◽  
Computing Services ◽  
The Face ◽  
Technological Developments ◽  
Hardware Resource ◽  
Short Time ◽  
Computing Infrastructure

In the present scenario, the field of Information Technology(IT) is moving from physical storage to cloud storage as "cloud" providers deliver on-demand resources over the Internet. MEC's key idea is to provide an IT infrastructure system and cloud computing services at the mobile network's edge, within the RAN and close to mobile users. MEC expands the idea of cloud computing by taking the benefits of the cloud closer to consumers in the form of a network edge, resulting in less latency from end to end. It is a decentralized computing infrastructure where some applications use signal processing, storage, control and computing are distributed between the data source and the cloud in the most effective and logical way. Virtualization is the main cloud infrastructure technology used in MEC. Virtualization is accomplished by virtualizing the software or hardware resource layer. Virtualization in MEC can be done by the hypervisor, Virtual machine, Docker Container or by Kubernetes. Hypervisors and VMs are the technologies used earlier. Docker is the technology we use nowadays, and Kubernetes is the future of Virtualization. In the face of large-scale and highly scalable needs, the cloud computing infrastructure is hard to fulfil in a short time, and the conventional virtual machine-based cloud host absorbs a lot of device resources on its own hence in this paper, we will address Docker as new container technology and introduce you to how this technology has solved previous problems in Virtualization, including the creation and deployment of large applications. The purpose of this paper is to provide a detailed survey of related MEC research and technological developments where specifically relevant research and future directions are illustrated.

scholarly journals Integration of Linux Containers in OpenStack: An Introspection

2018 ◽  
Vol 12 (3) ◽  
pp. 1094 ◽  
Author(s):  
Ashish Lingayat ◽  
Ranjana R. Badre ◽  
Anil Kumar Gupta
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Operating Systems ◽  
Virtual Machines ◽  
Cloud Provider ◽  
Storage Space ◽  
Computational Power ◽  
Management Tools ◽  
Additional Layer ◽  
Linux Containers

<p>In cloud computing, sharing of resources is supported using heavy weighted traditional virtualization techniques. Such techniques involve hypervisors to emulate hardware for creating virtual machines. The inclusion of an additional layer of hypervisor over host operating system depreciates the performance of the virtual machine. Recent evolution is a lightweight alternative to the virtual machine called containers which have gained<br />popularity among developers and administrators. Container Based virtualization has proven very efficient regarding performance, and many industries are now migrating their virtualized environment to run on Linux containers. Containers use host operating systems kernel and isolate each container by encapsulating them with their required services and packages. Linux kernel is very beneficial in implementing containers, which is the reason for the existence of Linux containers. Linux containers utilize less storage space and consume optimal computational power, giving a hike in performance. Having them integrated into the cloud surely benefits consumer and cloud provider. Many projects have extended their support in incorporating containers in the cloud. In this paper, we will discuss various Linux containers and their management tools along with cloud computing software, OpenStack, including projects undertaken by OpenStack for integrating containers in the cloud.</p>

Dynamic Programming Inspired Virtual Machine Instances Allocation in Cloud Computing

2017 ◽  
Vol 14 (1) ◽  
pp. 551-560 ◽  
Author(s):  
P Karthikeyan ◽  
M Chandrasekaran
Keyword(s):  
Cloud Computing ◽  
Dynamic Programming ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Cloud Provider ◽  
Revenue Generation ◽  
On Demand ◽  
Allocation Method ◽  
Cloud Environments ◽  
Time And Space Complexity

Cloud computing provides virtual machines instances to the user for performing various computational tasks on demand for a specific period of time. Considering the architecture and characteristics of the cloud environments, traditional virtual machine instances allocation algorithms cannot be applied to the cloud environment appropriately. In this paper, we propose Dynamic programming inspired virtual machine instances allocation algorithm which allocates virtual machine instances to the user based on demand. The aim of this algorithm is to maximize the cloud provider’s revenue. We have mainly focused on the total revenue generation of the cloud provider and percentage of user served rather than focusing on running time and space complexity of the virtual machine instances allocation problem. We evaluate the proposed mechanism by performing simulations. The experimental results show that the proposed Dynamic programming inspired virtual machine instances allocation method provided a higher revenue generation for the cloud provider than traditional fixed price and combinatorial auction greedy virtual machine instances allocation method.

scholarly journals Intelligent Virtual Machine Provisioning in Cloud Computing

2020 ◽  
Author(s):  
Chuan Luo ◽  
Bo Qiao ◽  
Xin Chen ◽  
Pu Zhao ◽  
Randolph Yao ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Resource Constraints ◽  
Bayesian Optimization ◽  
Prediction Uncertainty ◽  
Long Time ◽  
Practical Performance ◽  
Virtual Machine Provisioning ◽  
Public Datasets ◽  
Vm Provisioning

Virtual machine (VM) provisioning is a common and critical problem in cloud computing. In industrial cloud platforms, there are a huge number of VMs provisioned per day. Due to the complexity and resource constraints, it needs to be carefully optimized to make cloud platforms effectively utilize the resources. Moreover, in practice, provisioning a VM from scratch requires fairly long time, which would degrade the customer experience. Hence, it is advisable to provision VMs ahead for upcoming demands. In this work, we formulate the practical scenario as the predictive VM provisioning (PreVMP) problem, where upcoming demands are unknown and need to be predicted in advance, and then the VM provisioning plan is optimized based on the predicted demands. Further, we propose Uncertainty-Aware Heuristic Search (UAHS) for solving the PreVMP problem. UAHS first models the prediction uncertainty, and then utilizes the prediction uncertainty in optimization. Moreover, UAHS leverages Bayesian optimization to interact prediction and optimization to improve its practical performance. Extensive experiments show that UAHS performs much better than state-of-the-art competitors on two public datasets and an industrial dataset. UAHS has been successfully applied in Microsoft Azure and brought practical benefits in real-world applications.

Short-Time Tests for Long-Time Endurance

1923 ◽  
Vol 128 (4) ◽  
pp. 264-264
Author(s):  
J. W. Harsch
Keyword(s):  
Long Time ◽  
Short Time

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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