Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks
Thesis (PhD (Computer Engineering))--University of Pretoria, 2021.
Saved in:
| Other Authors: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
University of Pretoria
2021
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613459815858176 |
|---|---|
| access_status_str | Open Access |
| author2 | Malekian, Reza |
| author_browse | Malekian, Reza |
| author_facet | Malekian, Reza |
| collection | Thesis |
| dc_rights_str_mv | © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD (Computer Engineering))--University of Pretoria, 2021. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/78709 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:29.578Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/78709 SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks Malekian, Reza owoicho.ijiga@gmail.com Okonkwo, Uche Ijiga, Owoicho Emmanuel UCTD Channel Estimation Data Rate Emergent Configurations Multi Path Propagation Software Defined Networking Thesis (PhD (Computer Engineering))--University of Pretoria, 2021. Several heterogeneous, intelligent and distributed devices can be connected to interact with one another over the internet in what is known as the internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for increasing the production output of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). More so, the benefits of IoT technology can be particularly exploited across the maritime industry in what is termed the internet of maritime things (IoMT) where sensors and actuator devices are implanted on marine equipment in order to foster the communication efficacy of nautical radio networks. Marine explorations may suffer from unwanted situations such as transactional delays, environmental degradation, insecurity, seaport congestions, accidents and collisions etc, which could arise from severe environmental conditions. As a result, there is a need to develop proper communication techniques that will improve the overall quality of service (QoS) and quality of experience (QoE) of marine users. To address these, the merits of contemporaneous technologies such as ubiquitous computing, software-defined networking (SDN) and network functions virtualization (NFV) in addition to salubrious communication techniques including emergent configurations (EC), channel estimation (CE) and communication routing protocols etc, can be utilized for sustaining optimal operation of pelagic networks. Emergent configuration (EC) is a technology that can be adapted into maritime radio networks to support the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this thesis, a survey on the concept of IoT is presented in addition to a review of IIoT systems. The applications of ubiquitous computing and SDN technology are employed to design a newfangled network architecture which is specifically propounded for enhancing the throughput of oil and gas production in the maritime ecosystem. The components of this architecture work in collaboration with one another by attempting to manage and control the exploration process of deep ocean activities especially during emergencies involving anthropogenic oil and gas spillages. Several heterogeneous, intelligent and distributed devices can be connected to interact with one another over the internet in what is known as the internet of things (IoT). Also, the concept of IoT can be exploited in the industrial environment for increasing the production output of goods and services and for mitigating the risk of disaster occurrences. This application of IoT for enhancing industrial production is known as industrial IoT (IIoT). More so, the benefits of IoT technology can be particularly exploited across the maritime industry in what is termed the internet of maritime things (IoMT) where sensors and actuator devices are implanted on marine equipment in order to foster the communication efficacy of nautical radio networks. Marine explorations may suffer from unwanted situations such as transactional delays, environmental degradation, insecurity, seaport congestions, accidents and collisions etc, which could arise from severe environmental conditions. As a result, there is a need to develop proper communication techniques that will improve the overall quality of service (QoS) and quality of experience (QoE) of marine users. To address these, the merits of contemporaneous technologies such as ubiquitous computing, software-defined networking (SDN) and network functions virtualization (NFV) in addition to salubrious communication techniques including emergent configurations (EC), channel estimation (CE) and communication routing protocols etc, can be utilized for sustaining optimal operation of pelagic networks. Emergent configuration (EC) is a technology that can be adapted into maritime radio networks to support the operation and collaboration of IoT connected devices in order to improve the efficiency of the connected IoT systems for maximum user satisfaction. To meet user goals, the connected devices are required to cooperate with one another in an adaptive, interoperable, and homogeneous manner. In this thesis, a survey on the concept of IoT is presented in addition to a review of IIoT systems. The applications of ubiquitous computing and SDN technology are employed to design a newfangled network architecture which is specifically propounded for enhancing the throughput of oil and gas production in the maritime ecosystem. The components of this architecture work in collaboration with one another by attempting to manage and control the exploration process of deep ocean activities especially during emergencies involving anthropogenic oil and gas spillages. On the other hand, CE is a utilitarian communication technique that can be exploited during maritime exploration processes which offer additional reinforcement to the capacities of the nautical radio network. This technique enables the receivers of deep-sea networks to efficiently approximate the channel impulse response (CIR) of the wireless communication channel so that the effects of the communication channel on the transmitting aggregated cluster head information can be proficiently understood and predicted for useful decision-making procedures. Two CE schemes named inter-symbol interference/ average noise reduction (ISI/ANR) and reweighted error-reducing (RER) are designed in this study for estimating maritime channels for supporting the communication performances of nautical radio networks in both severe and light-fading environmental conditions. In the proposed RER method, the Manhattan distance of the CIR of an orthodox adaptive estimator is taken, which is subsequently normalised by a stability constant ɛ whose responsibility is for correcting any potential numerical system instability that may arise during the updating stages of the estimation process. To decrease the received signal error, a log-sum penalty function is eventually multiplied by an adjustable leakage (ɛ ) ̈that provides additional stability to the oscillating channel behaviour. The performance of the proposed RER method is further strengthened and made resilient against channel effects by the introduction of a reweighting attractor that further contracts the mean square error of this proposed estimator. In the ISI/ANR technique, the effects of possible ISI that may arise from maritime transmissions is considered and transformed using a low-pass filter that is incorporated for eliminating the effects of channel noise possible effects of multipath propagation. The RER scheme offered superior CE performances in comparison to other customary techniques such as the adaptive recursive least squares and normalised least mean square method in addition to conventional linear approaches such as least squares, linear minimum mean square error and maximum-likelihood estimation method. The proposed ISI/ANR technique offered an improved MSE performance in comparison to all considered linear methods. Finally, from this study, we were able to establish that accurate CE methods can improve the QoS and QoE of nautical radio networks in terms of network data rate and system outage probability. University of Pretoria Doctoral research grant, South African National Research Foundation/Research and Innovation Support and Advancement (NRF/RISA) research grant. Center for Connected Intelligence, Advanced Sensor Networks research group, University of Pretoria. Electrical, Electronic and Computer Engineering PhD (Computer Engineering) Unrestricted 2021-02-17T08:47:24Z 2021-02-17T08:47:24Z 2021-04-19 2021 Thesis Ijiga, OE 2021, SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd http://hdl.handle.net/2263/78709 A2021 http://hdl.handle.net/2263/78709 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Channel Estimation Data Rate Emergent Configurations Multi Path Propagation Software Defined Networking SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title | SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title_full | SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title_fullStr | SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title_full_unstemmed | SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title_short | SDN-based adaptive data-enabled channel estimation in the internet of maritime things for QoS enhancement in nautical radio networks |
| title_sort | sdn based adaptive data enabled channel estimation in the internet of maritime things for qos enhancement in nautical radio networks |
| topic | UCTD Channel Estimation Data Rate Emergent Configurations Multi Path Propagation Software Defined Networking |
| url | http://hdl.handle.net/2263/78709 |