scholarly journals Prototipo IaaS para el estudio del almacenamiento en bloque basado en Cinder

2019 ◽  
pp. 21-26
Author(s):  
Dennise Ivonne Gallardo-Alvarez ◽  
Juan Pablo Razón-González ◽  
Israel Durán-Belman ◽  
Juan Antonio Magdaleno Zavala
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Virtual Machines ◽  
The Other ◽  
Cloud Platform ◽  
Test Environment ◽  
New Era ◽  
Key Factor ◽  
Evolution Of Technology ◽  
Block Storage

The evolution of technology towards a new era of agile and dynamic workflows in the topic of cloud computing has resulted in professionals in Information Technology deepening in the study of tools or mechanisms that optimize the storage and data security; on the other hand, for companies that increasingly handle a larger volume of data to develop their activity, having these tools has become a key factor today. In this work is present the study of the Cinder component of the OpenStack platform, as a block storage tool that is associated with virtual machines or instances; is presented the deployment of a cloud platform of the IaaS model (Infrastructure as a Service) in a test environment, following the first four phases of the PDIOO methodology proposed by Cisco Systems; and the results that demonstrate the persistent storage of information through the use of said component are presented.

scholarly journals Viability of Cloud Computing for Real-Time Numerical Weather Prediction

2016 ◽  
Vol 31 (6) ◽  
pp. 1985-1996 ◽  
Author(s):  
David Siuta ◽  
Gregory West ◽  
Henryk Modzelewski ◽  
Roland Schigas ◽  
Roland Stull
Keyword(s):  
Cloud Computing ◽  
High Performance Computing ◽  
Real Time ◽  
Numerical Weather Prediction ◽  
High Performance ◽  
Virtual Machines ◽  
Weather Prediction ◽  
Cloud Platform ◽  
Numerical Weather ◽  
Performance Computing

Abstract As cloud-service providers like Google, Amazon, and Microsoft decrease costs and increase performance, numerical weather prediction (NWP) in the cloud will become a reality not only for research use but for real-time use as well. The performance of the Weather Research and Forecasting (WRF) Model on the Google Cloud Platform is tested and configurations and optimizations of virtual machines that meet two main requirements of real-time NWP are found: 1) fast forecast completion (timeliness) and 2) economic cost effectiveness when compared with traditional on-premise high-performance computing hardware. Optimum performance was found by using the Intel compiler collection with no more than eight virtual CPUs per virtual machine. Using these configurations, real-time NWP on the Google Cloud Platform is found to be economically competitive when compared with the purchase of local high-performance computing hardware for NWP needs. Cloud-computing services are becoming viable alternatives to on-premise compute clusters for some applications.

scholarly journals The Study of Data Security in Cloud Computing

2020 ◽  
Vol 4 (4) ◽  
Author(s):  
Abdullahi Abubakar ◽  
Alhaji Idi Babate ◽  
Abdulhakeem Ishola ◽  
Asma’u Muhammad Sani
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Virtual Machines ◽  
Successful Implementation ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Security Issues ◽  
It Architecture ◽  
The World ◽  
And Control

Cloud computing holds the possibility to annihilate the needs for setting up of costly computing infrastructure for IT-based services and proffering IT Solutions.  It offers an adaptable IT architecture which is accessible via the internet for lightweight and hand-held compact gadgets. The concept has encouraged numerous folds to improve in the capacity or capabilities of the existing and new software. In the cloud computing environment, the whole data/information is available over a set of networked resources, empowering the information to be accessible via virtual machines. Considering the fact that the cloud computing server may be located in any part of the world beyond the reach and control of users, there are various security issues and privacy challenges that need to be clearly understood with a view to identifying how to mitigate them.  Likewise, there are possibilities of the imminent breakdown of servers which have been witnessed in recent times. This research addresses the security issues connected with cloud computing, provides analysis of the militating factors against the successful implementation of cloud computing and proffers useful recommendations on how to ameliorate identified issues.

Internet-Based Virtual Computing Infrastructure for Cloud Computing

2013 ◽  
pp. 371-389 ◽  
Author(s):  
James Hardy ◽  
Lu Liu ◽  
Cui Lei ◽  
Jianxin Li
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
The Internet ◽  
Test Environment ◽  
Office Environment ◽  
Virtual Computing ◽  
Virtual Machine Cloning ◽  
State Of Art ◽  
Computing Infrastructure

Virtualisation is massively important in computing and continues to develop. This chapter discusses and evaluates the virtualisation technologies and in particular, a state-of-art system called iVIC (the Internet-based Virtual Computing) developed by Beihang University, China as it provides an all-in-one example of many of the major headline Cloud Computing titles of SaaS, IaaS, and HaaS. The chapter considers several virtualization packages which are either commercial, community, or experimental, before focusing on iVIC, a virtual machine cloning system that may be beneficial in a learning or office environment. The chapter introduces a test environment which is used to assess the performance of the iVIC process and the virtual machines created. Power requirements of virtual, as opposed to physical machines, are compared and evaluated. The chapter closes with conclusions regarding virtualisation and iVIC.

scholarly journals Tech report: Orchestrating your cloud orchestra: Model driven development of cloud deployment and orchestration for distributed computer music instruments

2015 ◽  
Author(s):  
Abram Hindle
Keyword(s):  
Cloud Computing ◽  
Computer Music ◽  
Virtual Machines ◽  
Music Performance ◽  
Large Computer ◽  
Model Driven Development ◽  
New Era ◽  
Model Driven ◽  
Start Up ◽  
Development Approach

Cloud computing potentially ushers in a new era of computer music performance with exceptionally large computer music instruments consisting of 10s to 100s of virtual machines called a Cloud Orchestra. Cloud computing allows for the rapid provisioning of resources, but to deploy such a complicated and interconnected network of software synthesizers in the cloud requires a lot of manual work, system administration knowledge, and devops (developer-sysop) skills. This is a barrier to computer musicians whose goal is to produce and perform music, and not to sysadmin 100s of computers. This work discusses the issues facing cloud orchestra deployment and offers an abstract solution and a concrete implementation. The abstract solution is generate cloud orchestra deployment plans by allowing computer musicians to model their network of synthesizers and to describe their resources. A model optimizer will compute near-optimal deployment plans to synchronize, deploy, and orchestrate the start-up of a complex network of synthesizers deployed to many computers. This model driven development approach frees computer musicians from much of the hassle of deployment and allocation. Computer musicians can focus on the configuration of musical components and leave the resource allocation up to the modelling software to optimize.

Role of Agents to Enhance the Security and Scalability in Cloud Environment

2019 ◽  
pp. 552-573 ◽  
Author(s):  
Manisha Malhotra ◽  
Aarti Singh
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Mobile Agents ◽  
The Other ◽  
Main Concern ◽  
Hybrid Architecture ◽  
Cloud Environment ◽  
Dynamic Nature ◽  
The One

Cloud computing is a novel paradigm that changes the industry viewpoint of inventing, developing, deploying, scaling, updating, maintaining, and paying for applications and the infrastructure on which they are deployed. Due to dynamic nature of cloud computing it is quite easy to increase the capacity of hardware or software, even without investing on purchases of it. This feature of cloud computing is named as scalability which is one of the main concern in cloud environment. This chapter presents the architecture of scalability by using mobile agents. It also highlights the other main issues prevailing in cloud paradigm. Further it presents the hybrid architecture for data security which is also the one of major concern of it. This chapter mainly highlights the solution for scalability and security.

scholarly journals HYBRIDIZATION OF RSA AND BLOWFISH CRYPTOGRAPHY ALGORITHMS FOR DATA SECURITY ON CLOUD STORAGE

2020 ◽  
Vol 6 (12) ◽  
pp. 29-34
Author(s):  
Isiaka O.S. ◽  
Murtala K. ◽  
Ibraheem A.F. ◽  
Bolaji-Adetoro D.F.
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Cloud Storage ◽  
The Other ◽  
Authorized User ◽  
Cryptographic Algorithms ◽  
Different Types

Security is provided for data according to the requirements of client. Cloud computing provides different types of services. Apart from the advantages of cloud, it has many security related issues. The topmost challenge in cloud is data security. There are more possibilities that the data are accessed by the other users of cloud storage. Data security must be addressed in the cloud storage. Cryptography is the most known technique for securing the data by encryption. It is necessary to propose encryption techniques which are suitable for cloud storage. Every cloud computing provides the different level of security. The aim of this study is to improve on the security of data or file stored on cloud storage using hybrid cryptographic algorithms for encryption. The algorithms are designed in such a way that one authenticates the authorized user and the other provides confidentiality and security for data stored on cloud.

scholarly journals DisOpenFaaS: A Distributed Function-as-a-Service Platform

2019 ◽  
Author(s):  
Lucas Vieira ◽  
Adbys Vasconcelos ◽  
Ítalo Batista ◽  
Rodolfo A. M. Silva ◽  
Francisco Brasileiro
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Platform ◽  
Service Model ◽  
Service Platform ◽  
Hybrid Clouds ◽  
Cloud Computing Service ◽  
Low Costs ◽  
Auto Scaling ◽  
Distributed Infrastructure

The adoption of cloud computing is increasing due to low costs of infrastructure, as well as having virtually infinite resources available for demand based scaling. The increasing interest in this topic, there is a continuous search for better ways to manage such infrastructures. One of the most recent steps was the development of Function-as-a-Service (FaaS). FaaS is a cloud computing service model where developers can deploy functions to a cloud platform and have them executed based on the triggering of events, or by making HTTP(S) requests. We propose an architecture for deploying FaaS platforms in hybrid clouds that can be composed by multiple cloud providers. This architecture enable privately deployed FaaS platforms to perform auto-scaling of virtual machines in a distributed infrastructure, while considering the scenario where the users of such platform are scattered around the globe. This allows the execution of requests in servers geographically located as close as possible from the client.

scholarly journals Tech report: Orchestrating your cloud orchestra: Model driven development of cloud deployment and orchestration for distributed computer music instruments

2015 ◽  
Author(s):  
Abram Hindle
Keyword(s):  
Cloud Computing ◽  
Computer Music ◽  
Virtual Machines ◽  
Music Performance ◽  
Large Computer ◽  
Model Driven Development ◽  
New Era ◽  
Model Driven ◽  
Start Up ◽  
Development Approach

Cloud computing potentially ushers in a new era of computer music performance with exceptionally large computer music instruments consisting of 10s to 100s of virtual machines called a Cloud Orchestra. Cloud computing allows for the rapid provisioning of resources, but to deploy such a complicated and interconnected network of software synthesizers in the cloud requires a lot of manual work, system administration knowledge, and devops (developer-sysop) skills. This is a barrier to computer musicians whose goal is to produce and perform music, and not to sysadmin 100s of computers. This work discusses the issues facing cloud orchestra deployment and offers an abstract solution and a concrete implementation. The abstract solution is generate cloud orchestra deployment plans by allowing computer musicians to model their network of synthesizers and to describe their resources. A model optimizer will compute near-optimal deployment plans to synchronize, deploy, and orchestrate the start-up of a complex network of synthesizers deployed to many computers. This model driven development approach frees computer musicians from much of the hassle of deployment and allocation. Computer musicians can focus on the configuration of musical components and leave the resource allocation up to the modelling software to optimize.

Classification of File Data Based on Confidentiality in Cloud Computing using K-NN Classifier

2016 ◽  
Vol 3 (2) ◽  
pp. 61-78 ◽  
Author(s):  
Munwar Ali Zardari ◽  
Low Tang Jung
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Virtual Machine ◽  
Data Security ◽  
Virtual Machines ◽  
Data Classification ◽  
Data Encryption ◽  
Cloud Services ◽  
Security Level ◽  
Public Data

Cloud computing is a new paradigm model that offers different services to its customers. The increasing number of users for cloud services i.e. software, platform or infrastructure is one of the major reasons for security threats for customers' data. Some major security issues are highlighted in data storage service in the literature. Data of thousands of users are stored on a single centralized place where the possibility of data threat is high. There are many techniques discussed in the literature to keep data secure in the cloud, such as data encryption, private cloud and multiple clouds concepts. Data encryption is used to encrypt the data or change the format of the data into the unreadable format that unauthorized users could not understand even if they succeed to get access of the data. Data encryption is very expensive technique, it takes time to encrypt and decrypt the data. Deciding the security approach for data security without understanding the security needs of the data is a technically not a valid approach. It is a basic requirement that one should understand the security level of data before applying data encryption security approach. To discover the data security level of the data, the authors used machine learning approach in the cloud. In this paper, a data classification approach is proposed for the cloud and is implemented in a virtual machine named as Master Virtual Machine (Vmm). Other Vms are the slave virtual machines which will receive from Vmm the classified information for further processing in cloud. In this study the authors used three (3) virtual machines, one master Vmm and two slaves Vms. The master Vmm is responsible for finding the classes of the data based on its confidentiality level. The data is classified into two classes, confidential (sensitive) and non-confidential (non-sensitive/public) data using K-NN algorithm. After classification phase, the security phase (encryption phase) shall encrypt only the confidential (sensitive) data. The confidentiality based data classification is using K-NN in cloud virtual environment as the method to encrypt efficiently the only confidential data. The proposed approach is efficient and memory space friendly and these are the major findings of this work.

Classification of File Data Based on Confidentiality in Cloud Computing Using K-NN Classifier

2019 ◽  
pp. 678-697
Author(s):  
Munwar Ali Zardari ◽  
Low Tang Jung
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Security ◽  
Virtual Machines ◽  
Data Classification ◽  
Data Encryption ◽  
Security Level ◽  
New Paradigm ◽  
Memory Space ◽  
Multiple Clouds

Cloud computing is a new paradigm model that offers different services to its customers. The increasing number of users for cloud services i.e. software, platform or infrastructure is one of the major reasons for security threats for customers' data. Some major security issues are highlighted in data storage service in the literature. Data of thousands of users are stored on a single centralized place where the possibility of data threat is high. There are many techniques discussed in the literature to keep data secure in the cloud, such as data encryption, private cloud and multiple clouds concepts. Data encryption is used to encrypt the data or change the format of the data into the unreadable format that unauthorized users could not understand even if they succeed to get access of the data. Data encryption is very expensive technique, it takes time to encrypt and decrypt the data. Deciding the security approach for data security without understanding the security needs of the data is a technically not a valid approach. It is a basic requirement that one should understand the security level of data before applying data encryption security approach. To discover the data security level of the data, the authors used machine learning approach in the cloud. In this paper, a data classification approach is proposed for the cloud and is implemented in a virtual machine named as Master Virtual Machine (Vmm). Other Vms are the slave virtual machines which will receive from Vmm the classified information for further processing in cloud. In this study the authors used three (3) virtual machines, one master Vmm and two slaves Vms. The master Vmm is responsible for finding the classes of the data based on its confidentiality level. The data is classified into two classes, confidential (sensitive) and non-confidential (non-sensitive/public) data using K-NN algorithm. After classification phase, the security phase (encryption phase) shall encrypt only the confidential (sensitive) data. The confidentiality based data classification is using K-NN in cloud virtual environment as the method to encrypt efficiently the only confidential data. The proposed approach is efficient and memory space friendly and these are the major findings of this work.

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