Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Flexible network management in software defined wireless sensor networks for monitoring application systems
Thesis (PhD)--University of Pretoria, 2018.
Saved in:
| Other Authors: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
University of Pretoria
2018
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613577228058624 |
|---|---|
| access_status_str | Open Access |
| author2 | Malekian, Reza |
| author_browse | Malekian, Reza |
| author_facet | Malekian, Reza |
| collection | Thesis |
| dc_rights_str_mv | © 2018 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)--University of Pretoria, 2018. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/66016 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:38:21.509Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| 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:2263/66016 Flexible network management in software defined wireless sensor networks for monitoring application systems Malekian, Reza lekgotla.magivo@gmail.com Modieginyane, Kgotlaetsile Mathews Software Defined Wireless Sensor Networking UCTD Thesis (PhD)--University of Pretoria, 2018. Wireless Sensor Networks (WSNs) are the commonly applied information technologies of modern networking and computing platforms for application-specific systems. Today’s network computing applications are faced with high demand of reliable and powerful network functionalities. Hence, efficient network performance is central to the entire ecosystem, more especially where human life is a concern. However, effective management of WSNs remains a challenge due to problems supplemental to them. As a result, WSNs application systems such as in monitored environments, surveillance, aeronautics, medicine, processing and control, tend to suffer in terms of capacity to support compute intensive services due to limitations experienced on them. A recent technology shift proposes Software Defined Networking (SDN) for improving computing networks as well as enhancing network resource management, especially for life guarding systems. As an optimization strategy, a software-oriented approach for WSNs, known as Software Defined Wireless Sensor Network (SDWSN) is implemented to evolve, enhance and provide computing capacity to these resource constrained technologies. Software developmental strategies are applied with the focus to ensure efficient network management, introduce network flexibility and advance network innovation towards the maximum operation potential for WSNs application systems. The need to develop WSNs application systems which are powerful and scalable has grown tremendously due to their simplicity in implementation and application. Their nature of design serves as a potential direction for the much anticipated and resource abundant IoT networks. Information systems such as data analytics, shared computing resources, control systems, big data support, visualizations, system audits, artificial intelligence (AI), etc. are a necessity to everyday life of consumers. Such systems can greatly benefit from the SDN programmability strategy, in terms of improving how data is mined, analysed and committed to other parts of the system for greater functionality. This work proposes and implements SDN strategies for enhancing WSNs application systems especially for life critical systems. It also highlights implementation considerations for designing powerful WSNs application systems by focusing on system critical aspects that should not be disregarded when planning to improve core network functionalities. Due to their inherent challenges, WSN application systems lack robustness, reliability and scalability to support high computing demands. Anticipated systems must have greater capabilities to ubiquitously support many applications with flexible resources that can be easily accessed. To achieve this, such systems must incorporate powerful strategies for efficient data aggregation, query computations, communication and information presentation. The notion of applying machine learning methods to WSN systems is fairly new, though carries the potential to enhance WSN application technologies. This technological direction seeks to bring intelligent functionalities to WSN systems given the characteristics of wireless sensor nodes in terms of cooperative data transmission. With these technological aspects, a technical study is therefore conducted with a focus on WSN application systems as to how SDN strategies coupled with machine learning methods, can contribute with viable solutions on monitoring application systems to support and provide various applications and services with greater performance. To realize this, this work further proposes and implements machine learning (ML) methods coupled with SDN strategies to; enhance sensor data aggregation, introduce network flexibility, improve resource management, query processing and sensor information presentation. Hence, this work directly contributes to SDWSN strategies for monitoring application systems. National Research Foundation (NRF) Telkom Centre of Excellence Electrical, Electronic and Computer Engineering PhD Unrestricted 2018-07-30T07:58:21Z 2018-07-30T07:58:21Z 2018-09-06 2018-02 Thesis Modieginyane, KM 2018, Flexible network management in software defined wireless sensor networks for monitoring application systems, PhD Thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/66016> S2018 http://hdl.handle.net/2263/66016 en © 2018 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 | Software Defined Wireless Sensor Networking UCTD Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title | Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title_full | Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title_fullStr | Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title_full_unstemmed | Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title_short | Flexible network management in software defined wireless sensor networks for monitoring application systems |
| title_sort | flexible network management in software defined wireless sensor networks for monitoring application systems |
| topic | Software Defined Wireless Sensor Networking UCTD |
| url | http://hdl.handle.net/2263/66016 |