Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020.
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Brac University
2021
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| Sarrera elektronikoa: | http://hdl.handle.net/10361/14405 |
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10361-144052021-04-21T21:01:15Z Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things Eusufzai, Fariha Haq, Tahmidul Chowdhury, Sumit Sahren, Shohani Sabuj, Saifur Rahman Rahman, Md. Mosaddequr Department of Electrical and Electronic Engineering, Brac University Cloud Computing Cognitive Radio Edge Computing Fog Computing Internet of Thing Reconfigurable Intelligent Surface This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020. Cataloged from PDF version of thesis. Includes bibliographical references (pages 32-40). Over the past decade, human interest in wireless communication has increased remarkably, and this has led to the development of the Internet of Things (IoT), Cloud, Fog, and Edge Computing. Existing wireless network models face several problems: low mobility, shortage of storage space, and slow data transfer speed due to the increased data traffic. As 127 new IoT devices are connected to the web every second, finding the solution to these problems has become a necessity. To improve the baud rate, Cognitive Radio was introduced, allowing the signals to select the shortest possible route during transmission. This paper proposes a model for CIoT-Fog-Cloud networking and the Reconfigurable Intelligent Surface (RIS) framework to resolve some of the problems. Fog-Cloud computation and Fog-Fog computation are the two situations considered to explain that storage computation would be more efficient, owning to a reduced physical distance between the Fog Nodes. The simulation results provided signs of quicker data transfer with low energy consumption and less transmission time Fariha Eusufzai Tahmidul Haq Sumit Chowdhury Shohani Sahren B. Electrical and Electronic Engineering 2021-04-21T05:59:50Z 2021-04-21T05:59:50Z 2020 2020-10 Thesis ID: 19121146 ID: 16210009 ID: 16321034 ID: 16221010 http://hdl.handle.net/10361/14405 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 40 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
en_US |
| topic |
Cloud Computing Cognitive Radio Edge Computing Fog Computing Internet of Thing Reconfigurable Intelligent Surface |
| spellingShingle |
Cloud Computing Cognitive Radio Edge Computing Fog Computing Internet of Thing Reconfigurable Intelligent Surface Eusufzai, Fariha Haq, Tahmidul Chowdhury, Sumit Sahren, Shohani Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2020. |
| author2 |
Sabuj, Saifur Rahman |
| author_facet |
Sabuj, Saifur Rahman Eusufzai, Fariha Haq, Tahmidul Chowdhury, Sumit Sahren, Shohani |
| format |
Thesis |
| author |
Eusufzai, Fariha Haq, Tahmidul Chowdhury, Sumit Sahren, Shohani |
| author_sort |
Eusufzai, Fariha |
| title |
Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| title_short |
Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| title_full |
Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| title_fullStr |
Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| title_full_unstemmed |
Performance analysis of Fog and Cloud Nodes for Cognitive Internet of Things |
| title_sort |
performance analysis of fog and cloud nodes for cognitive internet of things |
| publisher |
Brac University |
| publishDate |
2021 |
| url |
http://hdl.handle.net/10361/14405 |
| work_keys_str_mv |
AT eusufzaifariha performanceanalysisoffogandcloudnodesforcognitiveinternetofthings AT haqtahmidul performanceanalysisoffogandcloudnodesforcognitiveinternetofthings AT chowdhurysumit performanceanalysisoffogandcloudnodesforcognitiveinternetofthings AT sahrenshohani performanceanalysisoffogandcloudnodesforcognitiveinternetofthings |
| _version_ |
1814307197764501504 |