Results and Discussions of Palm-Dorsa-Veins-Based Systems in the Cloud IoT-Based M-Health Environment

2021 ◽  
pp. 180-210
Keyword(s):  
Cloud Computing ◽  
Performance Evaluation ◽  
Critically Ill ◽  
Health Systems ◽  
Hardware Design ◽  
Identity Verification ◽  
Cloud Computing Environment ◽  
Median Filters ◽  
And Performance ◽  
Hardware Designs

The results of palm-dorsa-veins-based m-health systems in a cloud-computing environment are discussed and analyzed in a detailed way in this chapter of the book. The sample images S1, S2, S3, and S4 are being used for hardware designs and performance evaluation in the cases of re-sampling, segmentation, median filters, thinning and Top veins, which will be used for critically ill and general patients' identity verification in the cloud IoT-based m-health environments. The ModelSim-Altera hardware design language is used as a simulator tool to simulate the hardware design with sample veins images. Further, the ModelSim-Altera simulation outcomes are compared with MATLAB implementations for evaluating the performances of hardware designs of the described algorithms in the cloud IoT-based m-health environment. The outcomes are analyzed, and the details of these outcomes are discussed in this chapter.

Optimal Resource Usage in Multi-Cloud Computing Environment

2013 ◽  
Vol 3 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Veena Goswami ◽  
Choudhury Nishkanta Sahoo
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Queueing Network ◽  
Computing Environment ◽  
New Paradigm ◽  
Cloud Computing Environment ◽  
Optimal Resource ◽  
Optimal Resource Management ◽  
And Performance ◽  
Multi Cloud

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.

scholarly journals Distributed processing in virtual simulation using Cloud Computing Environment

2018 ◽  
Vol 210 ◽  
pp. 04018
Author(s):  
Jarosław Koszela ◽  
Maciej Szymczyk
Keyword(s):  
Cloud Computing ◽  
Distributed Processing ◽  
Simulation Models ◽  
Virtual Simulation ◽  
Performance Tests ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Detailed Simulation ◽  
And Performance

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.

An Optimal Resource Allocation Algorithm in Cloud Computing Environment

2015 ◽  
Vol 733 ◽  
pp. 779-783 ◽  
Author(s):  
Lu Dai ◽  
Jian Hua Li
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Optimization ◽  
Scientific Basis ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
Optimal Resource ◽  
And Performance

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.

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