RT-Cloud: Virtualization Technologies and Cloud Computing for Railway Use-Case

2021 ◽  
Author(s):  
Gautam Gala ◽  
Gerhard Fohler ◽  
Peter Tummeltshammer ◽  
Stefan Resch ◽  
Reinhard Hametner
Keyword(s):  
Cloud Computing ◽  
Use Case

Real Time Risk Management in Cloud Computation

2013 ◽  
pp. 123-145
Author(s):  
Kashif Kifayat ◽  
Thar Baker Shamsa ◽  
Michael Mackay ◽  
Madjid Merabti ◽  
Qi Shi
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Risk Management ◽  
Real Time ◽  
Use Case ◽  
The Real ◽  
Security Issues ◽  
Processing Resources ◽  
Cloud Computation ◽  
Time Assessment

The rise of Cloud Computing represents one of the most significant shifts in Information technology in the last 5 years and promises to revolutionise how we view the availability and consumption of computing storage and processing resources. However, it is well-known that along with the benefits of Cloud Computing, it also presents a number of security issues that have restricted its deployment to date. This chapter reviews the potential vulnerabilities of Cloud-based architectures and uses this as the foundation to define a set of requirements for reassessing risk management in Cloud Computing. To fulfill these requirements, the authors propose a new scheme for the real-time assessment and auditing of risk in cloud-based applications and explore this with the use case of a triage application.

Monitoring Services in a Federated Cloud

2012 ◽  
pp. 242-265 ◽  
Author(s):  
Stuart Clayman ◽  
Giovanni Toffetti ◽  
Alex Galis ◽  
Clovis Chapman
Keyword(s):  
Cloud Computing ◽  
Crystal Structures ◽  
Monitoring System ◽  
Computational Prediction ◽  
Use Case ◽  
Cloud Environment ◽  
Reservoir Architecture ◽  
Service Monitoring ◽  
Case Application ◽  
Service Cloud

This chapter presents the need, the requirements, and the design for a monitoring system that is suitable for supporting the operations and management of a Federated Cloud environment. The chapter discusses these issues within the context of the RESERVOIR Service Cloud computing project. It first presents the RESERVOIR architecture itself, then introduces the issues of service monitoring in a federated environment, together with the specific solutions that have been devised for RESERVOIR. It ends with a review of the authors’ experience in this area by showing a use-case application executing on RESERVOIR, which is responsible for the computational prediction of organic crystal structures.

Using Free Software for Elastic Web Hosting on a Private Cloud

2012 ◽  
pp. 733-748
Author(s):  
Roland Kübert ◽  
Gregory Katsaros
Keyword(s):  
Cloud Computing ◽  
Real Life ◽  
Free Software ◽  
Technical Solution ◽  
Use Case ◽  
Cloud Infrastructure ◽  
Private Cloud ◽  
Software Applications ◽  
Experimental Laboratory ◽  
And Storage

Even though public cloud providers already exist and offer computing and storage services, cloud computing is still a buzzword for scientists in various fields such as engineering, finance, social sciences, etc. These technologies are currently mature enough to leave the experimental laboratory in order to be used in real-life scenarios. To this end, the authors consider that the prime example use case of cloud computing is a web hosting service. This paper presents the architectural approach as well as the technical solution for applying elastic web hosting onto a private cloud infrastructure using only free software. Through several available software applications and tools, anyone can build their own private cloud on top of a local infrastructure and benefit from the dynamicity and scalability provided by the cloud approach.

Using Free Software for Elastic Web Hosting on a Private Cloud

2013 ◽  
pp. 97-111
Author(s):  
Roland Kübert ◽  
Gregory Katsaros
Keyword(s):  
Cloud Computing ◽  
Real Life ◽  
Free Software ◽  
Technical Solution ◽  
Use Case ◽  
Cloud Infrastructure ◽  
Private Cloud ◽  
Software Applications ◽  
Experimental Laboratory ◽  
And Storage

Even though public cloud providers already exist and offer computing and storage services, cloud computing is still a buzzword for scientists in various fields such as engineering, finance, social sciences, etc. These technologies are currently mature enough to leave the experimental laboratory in order to be used in real-life scenarios. To this end, the authors consider that the prime example use case of cloud computing is a web hosting service. This paper presents the architectural approach as well as the technical solution for applying elastic web hosting onto a private cloud infrastructure using only free software. Through several available software applications and tools, anyone can build their own private cloud on top of a local infrastructure and benefit from the dynamicity and scalability provided by the cloud approach.

scholarly journals Security issues and threats that may affect the hybrid cloud of FINESCE

2016 ◽  
Vol 8 (1) ◽  
pp. 26 ◽  
Author(s):  
Julia Sánchez ◽  
Guiomar Corral ◽  
Ramon Martín de Pozuelo ◽  
Agustín Zaballos
Keyword(s):  
Cloud Computing ◽  
Data Privacy ◽  
Energy Use ◽  
Distributed Storage ◽  
Future Internet ◽  
Energy System ◽  
Information And Communications Technology ◽  
Security Requirements ◽  
Use Case ◽  
Platform As A Service

FINESCE is the Smart Energy use case project of the Future Internet Public Private Partnership Programme. It aims at defining an open infrastructure based on Information and Communications Technology (ICT) used to develop new solutions and applications in all fields of Future Internet related to the energy sector. To accomplish this goal a cloud-based environment is proposed, providing high scalability, fast provisioning, resilience and cost efficiency, while facilitating the deployment of applications and services for utilities.The proposed solution for Smart Energy system encompasses Cloud Computing technologies taking advantage of the service delivery models that it provides (Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS)) over different cloud deployment solutions (Private, Public, Hybrid, Community). Therefore, it is necessary to study their implications, particularly with regard to security and data privacy, whether in transit or stored data, of the cloud solution chosen.The present paper aims to gather basic security requirements in deploying a solution based on Cloud Computing highlighting issues in hybrid clouds because this is the deployment model used in Smart Energy use case. It also exposes attacks and vulnerabilities related to Cloud Computing to be considered for implementing a secure environment for FIDEV, the private platform implementation. Moreover, the security requirements for Smart Energy use case are defined. And, finally, the results of a security audit performed over the testbed platform that simulates a distributed storage solution for FINESCE project are presented. 

Analysis of Genomic Data in a Cloud Computing Environment

Big Data ◽  
2016 ◽  
pp. 1129-1158
Author(s):  
Philip Groth ◽  
Gerhard Reuter ◽  
Sebastian Thieme
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Genomic Data ◽  
Security Requirements ◽  
Use Case ◽  
Shared Resources ◽  
Security Issues ◽  
Business Partners ◽  
Short Time

A new trend for data analysis in the life sciences is Cloud computing, enabling the analysis of large datasets in short time. This chapter introduces Big Data challenges in the genomic era and how Cloud computing can be one feasible approach for solving them. Technical and security issues are discussed and a case study where Clouds are successfully applied to resolve computational bottlenecks in the analysis of genomic data is presented. It is an intentional outcome of this chapter that Cloud computing is not essential for analyzing Big Data. Rather, it is argued that for the optimized utilization of IT, it is required to choose the best architecture for each use case, either by security requirements, financial goals, optimized runtime through parallelization, or the ability for easier collaboration and data sharing with business partners on shared resources.

Analysis of Genomic Data in a Cloud Computing Environment

2015 ◽  
pp. 186-214
Author(s):  
Philip Groth ◽  
Gerhard Reuter ◽  
Sebastian Thieme
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Genomic Data ◽  
Security Requirements ◽  
Use Case ◽  
Shared Resources ◽  
Security Issues ◽  
Business Partners ◽  
Short Time

A new trend for data analysis in the life sciences is Cloud computing, enabling the analysis of large datasets in short time. This chapter introduces Big Data challenges in the genomic era and how Cloud computing can be one feasible approach for solving them. Technical and security issues are discussed and a case study where Clouds are successfully applied to resolve computational bottlenecks in the analysis of genomic data is presented. It is an intentional outcome of this chapter that Cloud computing is not essential for analyzing Big Data. Rather, it is argued that for the optimized utilization of IT, it is required to choose the best architecture for each use case, either by security requirements, financial goals, optimized runtime through parallelization, or the ability for easier collaboration and data sharing with business partners on shared resources.

scholarly journals Simulation of Scalability in Cloud-Based IoT Reactive Systems Leveraged on a WSAN Simulator and Cloud Computing Technologies

2021 ◽  
Vol 11 (4) ◽  
pp. 1804
Author(s):  
Luis Jurado Pérez ◽  
Joaquín Salvachúa
Keyword(s):  
Cloud Computing ◽  
Modeling And Simulation ◽  
Simulation Model ◽  
Smart City ◽  
Hierarchical Modeling ◽  
Queuing System ◽  
Use Case ◽  
Sensors And Actuators ◽  
Iot Applications ◽  
Rapid Deployment

Implementing a wireless sensor and actuator network (WSAN) in Internet of Things (IoT) applications is a complex task. The need to establish the number of nodes, sensors, and actuators, and their location and characteristics, requires a tool that allows the preliminary determination of this information. Additionally, in IoT scenarios where a large number of sensors and actuators are present, such as in a smart city, it is necessary to analyze the scalability of these systems. Modeling and simulation can help to conduct an early study and reduce development and deployment times in environments such as a smart city. The design-time verification of the system through a network simulation tool is useful for the most complex and expensive part of the system formed by a WSAN. However, the use of real components for other parts of the IoT system is feasible by using cloud computing infrastructure. Although there are cloud computing simulators, the cloud layer is poorly developed for the requirements of IoT applications. Technologies around cloud computing can be used for the rapid deployment of some parts of the IoT application and software services using containers. With this framework, it is possible to accelerate the development of the real system, facilitate the rapid deployment of a prototype, and provide more realistic simulations. This article proposes an approach for the modeling and simulation of IoT systems and services in a smart city leveraged in a WSAN simulator and technologies of cloud computing. Our approach was verified through experiments with two use cases. (1) A model of sensor and actuator networks as an integral part of an IoT application to monitor and control parks in a city. Through this use case, we analyze the scalability of a system whose sensors constantly emit data. (2) A model for cloud-based IoT reactive parking lot systems for a city. Through our approach, we have created an IoT parking system simulation model. The model contains an M/M/c/N queuing system to simulate service requests from users. In this use case, the model replication through hierarchical modeling and scalability of a distributed parking reservation service were evaluated. This last use case showed how the simulation model could provide information to size the system through probability distribution variables related to the queuing system. The experimental results show that the use of simulation techniques for this type of application makes it possible to analyze scalability in a more realistic way.

scholarly journals Fog Computing: Issues, Challenges and Future Directions

2017 ◽  
Vol 7 (6) ◽  
pp. 3669 ◽  
Author(s):  
Prakash P ◽  
Darshaun K. G. ◽  
Yaazhlene. P ◽  
Medidhi Venkata Ganesh ◽  
Vasudha B
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Fog Computing ◽  
Low Latency ◽  
Use Case ◽  
Future Directions ◽  
Computing Power ◽  
Geographically Dispersed ◽  
Real Time Application ◽  
The Ideal

In Cloud Computing, all the processing of the data collected by the node is done in the central server. This involves a lot of time as data has to be transferred from the node to central server before the processing of data can be done in the server. Also it is not practical to stream terabytes of data from the node to the cloud and back. To overcome these disadvantages, an extension of cloud computing, known as fog computing, is introduced. In this, the processing of data is done completely in the node if the data does not require higher computing power and is done partially if the data requires high computing power, after which the data is transferred to the central server for the remaining computations. This greatly reduces the time involved in the process and is more efficient as the central server is not overloaded. Fog is quite useful in geographically dispersed areas where connectivity can be irregular. The ideal use case requires intelligence near the edge where ultra-low latency is critical, and is promised by fog computing. The concepts of cloud computing and fog computing will be explored and their features will be contrasted to understand which is more efficient and better suited for real-time application.

Improvement of QoS in an IoT Ecosystem by Integrating Fog Computing and SDN

2021 ◽  
Vol 11 (2) ◽  
pp. 48-66
Author(s):  
Ishtiaq Ahammad ◽  
Md. Ashikur Rahman Khan ◽  
Zayed Us Salehin ◽  
Main Uddin ◽  
Sultana Jahan Soheli
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
The Internet ◽  
Use Case ◽  
Qos Parameters ◽  
Almost All ◽  
Computation Load ◽  
The Internet Of Things ◽  
Network Form ◽  
Environmental Demands

The internet of things (IoT) creates immense volume of objects online. But cloud computing isn't suited to environmental demands. Hence, fog computing (FC) emerged which shifts the computation load into edge fog devices. However, FC also faces some obstacles which can be mitigated by software-defined networking (SDN). By combining SDN and FC, the network form can overcome almost all cloud limitations and can boost QoS. Within this article, architecture is proposed by combining SDN and FC to improve QoS for IoT ecosystem. With the architecture, an algorithm is propounded based on virtual partition. Then a use case is presented and evaluated through iFogSim simulator. The result shows a significant improvement of several QoS parameters in the execution of fog with SDN compared to the cloud-only execution. The results also show better results for energy consumption, network use (212.21% reduction), and latency (275.9% reduction) compared with previous similar use case.

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