scholarly journals On dynamic performance estimation of fault-prone Infrastructure-as-a-Service clouds

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771851 ◽  
Author(s):  
Wanbo Zheng ◽  
Yuandou Wang ◽  
Yunni Xia ◽  
Quanwang Wu ◽  
Lei Wu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Analytical Approach ◽  
Virtual Machines ◽  
Dynamic Performance ◽  
Rejection Rate ◽  
Performance Estimation ◽  
Variable Load ◽  
Infrastructure As A Service ◽  
Trend Prediction ◽  
Prediction Approach

The cloud computing paradigm enables elastic resources to be scaled at run time satisfy customers’ demand. Cloud computing provisions on-demand service to users based on a pay-as-you-go manner. This novel paradigm enables cloud users or tenant users to afford computational resources in the form of virtual machines as utilities, just like electricity, instead of paying for and building computing infrastructures by their own. Performance usually specified through service level agreement performance commitment of clouds is one of key research challenges and draws great research interests. Thus, performance issues of cloud infrastructures have been receiving considerable interest by both researchers and practitioners as a prominent activity for improving cloud quality. This work develops an analytical approach to dynamic performance modeling and trend prediction of fault-prone Infrastructure-as-a-Service clouds. The proposed analytical approach is based on a time-series and stochastic-process-based model. It is capable of predicting the expected system responsiveness and request rejection rate under variable load intensities, fault frequencies, multiplexing abilities, and instantiation processing times. A comparative study between theoretical and measured performance results through a real-world campus cloud is carried out to prove the correctness and accuracy of the proposed prediction approach.

scholarly journals Cloud-based Network Virtualization in IoT with OpenStack

2022 ◽  
Vol 22 (1) ◽  
pp. 1-26
Author(s):  
Zakaria Benomar ◽  
Francesco Longo ◽  
Giovanni Merlino ◽  
Antonio Puliafito
Keyword(s):  
Cloud Computing ◽  
Overlay Networks ◽  
Virtual Machines ◽  
Cloud Model ◽  
Network Virtualization ◽  
Bare Metal ◽  
Infrastructure As A Service ◽  
Model Network ◽  
The Core ◽  
Geographically Distributed

In Cloud computing deployments, specifically in the Infrastructure-as-a-Service (IaaS) model, networking is one of the core enabling facilities provided for the users. The IaaS approach ensures significant flexibility and manageability, since the networking resources and topologies are entirely under users’ control. In this context, considerable efforts have been devoted to promoting the Cloud paradigm as a suitable solution for managing IoT environments. Deep and genuine integration between the two ecosystems, Cloud and IoT, may only be attainable at the IaaS level. In light of extending the IoT domain capabilities’ with Cloud-based mechanisms akin to the IaaS Cloud model, network virtualization is a fundamental enabler of infrastructure-oriented IoT deployments. Indeed, an IoT deployment without networking resilience and adaptability makes it unsuitable to meet user-level demands and services’ requirements. Such a limitation makes the IoT-based services adopted in very specific and statically defined scenarios, thus leading to limited plurality and diversity of use cases. This article presents a Cloud-based approach for network virtualization in an IoT context using the de-facto standard IaaS middleware, OpenStack, and its networking subsystem, Neutron. OpenStack is being extended to enable the instantiation of virtual/overlay networks between Cloud-based instances (e.g., virtual machines, containers, and bare metal servers) and/or geographically distributed IoT nodes deployed at the network edge.

scholarly journals Taxonomy of resource allocation algorithms for inner IaaS cloud data centres

2013 ◽  
Author(s):  
Dang Minh Quan
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Virtual Machines ◽  
Computer Hardware ◽  
Infrastructure As A Service ◽  
Cloud Data ◽  
Cloud Infrastructures ◽  
Allocation Algorithms ◽  
Data Centres ◽  
Cloud User

Cloud computing has become more and more popular  with  the  widely  deployment  of  several  cloud infrastructures.  Infrastructure-as-a-service  (IaaS) Cloud  computing  replaces  bare  computer hardware. The cloud user  will use the virtual  machines (VMs)  to  fullfil  their  computing  requirements.  Among the  components  of  IaaS  cloud  software  stack,  the resource  allocation  module  is  very  important  as  it selects suitable VMs and the place to execute VMs. This paper  focuses  on  studying  and  classifying  algorithms used  in  the  resource  allocation  module.  The  issues  of how to apply those algorithms are also discussed.

scholarly journals The Needs of Virtual Machines Implementation in Private Cloud Computing Environment

2015 ◽  
Vol 6 (4) ◽  
pp. 525
Author(s):  
Edy Kristianto
Keyword(s):  
Cloud Computing ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Virtual Machines ◽  
Computing Environment ◽  
Infrastructure As A Service ◽  
Cloud Computing Environment ◽  
Information And Communication ◽  
Private Cloud Computing ◽  
The Internet Of Things

The Internet of Things (IOT) becomes the purpose of the development of information and communication technology. Cloud computing has a very important role in supporting the IOT, because cloud computing allows to provide services in the form of infrastructure (IaaS), platform (PaaS), and Software (SaaS) for its users. One of the fundamental services is infrastructure as a service (IaaS). This study analyzed the requirement that there must be based on a framework of NIST to realize infrastructure as a service in the form of a virtual machine to be built in a cloud computing environment.

scholarly journals Virtual machines migration game approach for multi-tier application in infrastructure as a service cloud computing

IET Networks ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 326-337
Author(s):  
Khiet Thanh Bui ◽  
Hung Dac Ho ◽  
Tran Vu Pham ◽  
Hung Cong Tran
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Infrastructure As A Service ◽  
Service Cloud

ANALISIS EFEKTIFITAS FRAMEWOK ERP CLOUD COMPUTING UNTUK USAHA KECIL MENENGAH

2018 ◽  
Vol 3 (1) ◽  
pp. 19 ◽  
Author(s):  
Matheus Alvian Wikanargo ◽  
Novian Adi Prasetyo ◽  
Angelina Pramana Thenata
Keyword(s):  
Cloud Computing ◽  
Human Resource ◽  
Software As A Service ◽  
Infrastructure As A Service ◽  
Computing Framework

AbstrakTeknologi cloud computing pada era sekarang berkembang pesat. Penerapan teknologi cloud computing sudah merambah ke berbagai industri, mulai dari perusahaan besar hingga perusahaan kecil dan menengah. Perambahan cloud computing di perindustrian berupa implementasi ke dalam sistem ERP. Namun, penetrasi teknologi ini dalam lingkup perusahaan kecil dan menengah (UKM) masih belum sekuat perusahaan besar. Penerapan ERP berbasis cloud computing yang masih tergolong baru tentu memiliki keuntungan dan penghambat yang mempengaruhi kinerja perusahaan. Hal tersebut menjadi salah satu pertimbangan UKM masih enggan menggunakan teknologi ini. Penelitian ini akan menganalisis framework yang paling sesuai untuk UKM dalam menerapkan sistem ERP berbasis cloud computing. Framework yang dianalisa yaitu Software as a Service (SaaS), Infrastructure as a Service (IaaS), dan Platform as as Service (PaaS). Ketiga framework ini akan dibandingkan menggunakan metode studi literatur. Tolak ukur yang menjadi acuan untuk perbandingan adalah Compatibility, Cost, Flexibility, Human Resource, Implementation, Maintenance, Security, dan Usability. Faktor-faktor tersebut akan diukur keuntungan dan penghambatnya jika diterapkan dalam SME. Hasil dari penilitian ini adalah Framework SaaS yang paling cocok untuk diterapkan pada perusahaan kecil dan menengah. Kata kunci— Cloud Computing, UKM, SaaS, IaaS, PaaS 

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

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.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

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