Analysis of Spectrum Utilization in Data Centers for Internet of Things

Citation

Roslee, Mardeni and Lee, Loo Chuan and Pang, Wai Leong and Anuar, Khairil (2021) Analysis of Spectrum Utilization in Data Centers for Internet of Things. In: 2021 IEEE 15th Malaysia International Conference on Communication (MICC), 1-2 Dec. 2021, Malaysia.

[img] Text
S2021_P128.pdf
Restricted to Repository staff only

Download (1MB)

Abstract

The Internet of Things is a collection of devices and machines that are capable of communicating with each other to manage industrial processes. The rise of the Internet of Things has resulted in many companies becoming more aware of the various benefits it can bring to their businesses. Many of these are implementing it to enhance their operations and customer service. The challenges are high complexity and low spectrum utilization. This issue is crucial and need to be optimized hence it require new model to represent the such system. This work is to provide an algorithm in order to reduce interference experienced by IoT nodes. The algorithm is developed to tackle the spectrum usage problem in order to decrease an interference. As a finding, due to interference and path loss between the IoT node system, the SINR values being affected where it decreases with increasing distance between nodes. The proposed algorithm showed that the dynamic spectrum shows better performance compared to in band and out band spectrum. With the dynamic spectrum, it gives better performance as well as better value of SINR.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: IoT, data center, spectrum
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 23 Feb 2022 03:48
Last Modified: 23 Feb 2022 03:48
URII: http://shdl.mmu.edu.my/id/eprint/9996

Downloads

Downloads per month over past year

View ItemEdit (login required)