Exploring On-Demand Composition of Pervasive Collaborations in Smart Computing Environments

2017 ◽  
pp. 305-314 ◽  
Author(s):  
Markus Wutzler
Keyword(s):  
On Demand ◽  
Computing Environments ◽  
Demand Composition ◽  
Smart Computing

A Security Framework for Secure Cloud Computing Environments

2019 ◽  
pp. 249-263 ◽  
Author(s):  
Mouna Jouini ◽  
Latifa Ben Arfa Rabai
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Security Risk ◽  
Security Issues ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Failure Cost ◽  
Computing Environments ◽  
Secure Cloud Computing ◽  
Security Risk Assessment

Cloud computing technology is a relatively new concept of providing scalable and virtualized resources, software and hardware on demand to consumers. It presents a new technology to deliver computing resources as a service. It offers a variety of benefits like services on demand and provisioning and suffers from several weaknesses. In fact, security presents a major obstacle in cloud computing adoption. In this paper, the authors will deal with security problems in cloud computing systems and show how to solve these problems using a quantitative security risk assessment model named Multi-dimensional Mean Failure Cost (M2FC). In fact, they summarize first security issues related to cloud computing environments and then propose a generic framework that analysis and evaluate cloud security problems and then propose appropriate countermeasures to solve these problems.

CONDE: Climate simulation ON DEmand using HPCaaS

2020 ◽  
Author(s):  
Diego A. Pérez Montes ◽  
Juan A. Añel ◽  
Javier Rodeiro
Keyword(s):  
Cloud Computing ◽  
Web Services ◽  
Climate Simulation ◽  
On Demand ◽  
Ensemble Simulations ◽  
Amazon Web Services ◽  
Computing Environments ◽  
Microsoft Azure

<p><strong>CONDE (Climate simulation ON DEmand)</strong> is the final result of our work and research about climate and meteorological simulations over an HPC as a Service (HPCaaS) model. On our architecture we run very large climate ensemble simulations using a, adapted, WRF version that is executed on-demand and that can be deployed over different Cloud Computing environments (like Amazon Web Services, Microsoft Azure or Google Cloud) and that uses BOINC as middleware for the tasks execution and results gathering. Here, we also present as well some basic examples of applications and experiments to verify that the simulations ran in our system are correct and show valid results. </p>

Security Problems in Cloud Computing Environments

2017 ◽  
pp. 70-103
Author(s):  
Mouna Jouini ◽  
Latifa Ben Arfa Rabai
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Assessment Model ◽  
Security Risk ◽  
Security Issues ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Failure Cost ◽  
Computing Environments ◽  
Security Risk Assessment

Cloud computing technology is a relatively new concept of providing scalable and virtualized resources, software and hardware on demand to consumers. It presents a new technology to deliver computing resources as a service. It offers a variety of benefits like services on demand and provisioning and suffers from several weaknesses. In fact security presents a major obstacle in cloud computing adoption. In this chapter, we will deal with security problems in cloud computing systems and show how to solve these problems using a quantitative security risk assessment model named Multi-dimensional Mean Failure Cost (M2FC). In fact, we present first a deep analysis of security issues related to cloud computing environments and then propose a generic framework that analysis and evaluate cloud security problems and then propose appropriate countermeasures to solve these problems.

A Security Framework for Secure Cloud Computing Environments

2016 ◽  
Vol 6 (3) ◽  
pp. 32-44 ◽  
Author(s):  
Mouna Jouini ◽  
Latifa Ben Arfa Rabai
Keyword(s):  
Cloud Computing ◽  
New Technology ◽  
Assessment Model ◽  
Security Risk ◽  
Security Issues ◽  
On Demand ◽  
Cloud Computing Adoption ◽  
Failure Cost ◽  
Computing Environments ◽  
Security Risk Assessment

Cloud computing technology is a relatively new concept of providing scalable and virtualized resources, software and hardware on demand to consumers. It presents a new technology to deliver computing resources as a service. It offers a variety of benefits like services on demand and provisioning and suffers from several weaknesses. In fact, security presents a major obstacle in cloud computing adoption. In this paper, the authors will deal with security problems in cloud computing systems and show how to solve these problems using a quantitative security risk assessment model named Multi-dimensional Mean Failure Cost (M2FC). In fact, they summarize first security issues related to cloud computing environments and then propose a generic framework that analysis and evaluate cloud security problems and then propose appropriate countermeasures to solve these problems.

scholarly journals Cost Optimization Algorithm for Data Center Management in Cloud

2019 ◽  
Vol 9 (2) ◽  
pp. 4778-4781
Keyword(s):  
Cloud Computing ◽  
Data Center ◽  
Benders Decomposition ◽  
Cost Optimization ◽  
Advance Reservation ◽  
Short Term ◽  
On Demand ◽  
Main Challenge ◽  
Computing Environments

One of the main challenge in cloud is Cost Optimization. In cloud computing, the cloud providers usually calls CSP offer provisioning plans for the cloud consumers in the following two ways one is reservation plan(also referred as long term plan) and the other is on-demand plan(also referred as short term plan). In general, cost of computing asset provisioned by reservation plan is cheaper when compared to cost obtained by the on-demand plan, With the reservation plan, the consumer can reduce the total asset provisioning cost since cloud consumer has to pay to provider in advance. However, the best advance reservation of assets is difficult to be accomplish due to uncertainty of cloud consumer’s future demand and providers’ resource prices. To address this problem, an OCRP algorithm is proposed by formulating a SPI model. The OCRP algorithm can provision computing assets for being used in multiple provisioning stages as well as a long-term plan. The demand and price uncertainty is considered in OCRP. In this project, different approaches to obtain the solution of the OCRP algorithm are considered including DEF, SAA and Benders decomposition. Numerical the studies are extensively performed in which the outcomes clearly show that with the OCRP algorithm, cloud consumer can successfully minimize total cost of asset provisioning in cloud computing environments

Scalable Vector Graphics (SVG) Based Multi-Level Graphics Representation for Engineering Rich-Content Exchange in Mobile Collaboration Computing Environments

2006 ◽  
Vol 6 (2) ◽  
pp. 96-102 ◽  
Author(s):  
Xiaoyong Su ◽  
B. S. Prabhu ◽  
Chi-Cheng Chu ◽  
Rajit Gadh
Keyword(s):  
Vector Graphics ◽  
Scalable Vector Graphics ◽  
On Demand ◽  
Engineering Collaboration ◽  
The Hierarchical Structure ◽  
Computing Environments ◽  
Multi Level ◽  
Multiple Levels ◽  
The Relationship ◽  
Rich Content

A two-dimensional (2D) graphics hierarchical representation framework and an on-demand content delivery mechanism for facilitating mobile engineering collaboration are presented in this paper. Multi-level graphics content sub-division is utilized to transform large engineering graphics into multiple levels of Scalable Vector Graphics (SVG) content. The hierarchical structure of the SVG content that maintains the relationship between the sub-divided content is formed during the process of sub-division. The divided content is selectively delivered and rendered on the mobile devices in an on-demand fashion. A prototypical system of the proposed approach is implemented and the performance of the framework is evaluated.

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