scholarly journals Implementation and performance evaluation of a distributed conjugate gradient method in a cloud computing environment

2012 ◽  
Vol 43 (3) ◽  
pp. 281-304 ◽  
Author(s):  
Leila Ismail ◽  
Rajeev Barua
2013 ◽  
Vol 3 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Veena Goswami ◽  
Choudhury Nishkanta Sahoo

Cloud computing has emerged as a new paradigm for accessing distributed computing resources such as infrastructure, hardware platform, and software applications on-demand over the internet as services. This paper presents an optimal resource management framework for multi-cloud computing environment. The authors model the behavior and performance of applications to integrate different service-providers for end-to-end-requirements. Each service model caters to specific type of requirements and there are already number of players with own customized products/services offered. Intercloud Federation and Service delegation models are part of Multi-Cloud environment where the broader target is to achieve infinite pool of resources. They propose an analytical queueing network model to improve the efficiency of the system. Numerical results indicate that the proposed provisioning technique detects changes in arrival pattern, resource demands that occur over time and allocates multiple virtualized IT resources accordingly to achieve application Quality of Service targets.


2018 ◽  
Vol 210 ◽  
pp. 04018
Author(s):  
Jarosław Koszela ◽  
Maciej Szymczyk

Today’s hardware has computing power allowing to conduct virtual simulation. However, even the most powerful machine may not be sufficient in case of using models characterized by high precision and resolution. Switching into constructive simulation causes the loss of details in the simulation. Nonetheless, it is possible to use the distributed virtual simulation in the cloud-computing environment. The aim of this paper is to propose a model that enables the scaling of the virtual simulation. The aspects on which the ability to disperse calculations depends were presented. A commercial SpatialOS solution was presented and performance tests were carried out. The use of distributed virtual simulation allows the use of more extensive and detailed simulation models using thin clients. In addition, the presented model of the simulation cloud can be the basis of the “Simulation-as-a-Service” cloud computing product.


2015 ◽  
Vol 733 ◽  
pp. 779-783 ◽  
Author(s):  
Lu Dai ◽  
Jian Hua Li

Resource allocation is a key technology of cloud computing. At present, the most of studies on resource allocation mainly focus on improving the overall performance by balancing the load of data center. This paper will design the experimental platform of resource allocation algorithm, energy optimization and performance analysis, obtain original achievements in scientific research ,for the resource allocation method based on immune algorithm and energy optimization in cloud computing to provide innovative ideas and scientific basis. This research has important significance for further study on resource allocation and energy optimization in cloud computing environment.


Cloud ecosystem basically offers Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Software as a Service (SaaS). This paper describes the testing process employed for testing the C-DAC cloud SuMegha. Though new tools for the testing cloud are emerging into the market, there are aspects which are suited for manual testing and some which can be speeded up using automated testing tools. This paper brings out the techniques best suited to test different features of Cloud computing environment. It offers a comparison of several tools which enhance the testing process at each level. The authors also try to bring out (recommend) broad guidelines to follow while setting up a cloud environment to reduce the number of bugs in the system


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