University of Cape TownUniversity of Cape Townhttp://repository.aust.edu.ng/xmlui/handle/123456789/40082024-03-28T09:08:30Z2024-03-28T09:08:30ZRobust and cheating-resilient power auctioning on Resource Constrained Smart Micro-GridsMarufu, Mufudzi Anesu Chapmanhttp://repository.aust.edu.ng/xmlui/handle/11427/284142018-11-26T13:54:29Z2018-01-01T00:00:00ZRobust and cheating-resilient power auctioning on Resource Constrained Smart Micro-Grids
Marufu, Mufudzi Anesu Chapman
The principle of Continuous Double Auctioning (CDA) is known to provide an efficient way of matching supply and demand among distributed selfish participants with limited information. However, the literature indicates that the classic CDA algorithms developed for grid-like applications are centralised and insensitive to the processing resources capacity, which poses a hindrance for their application on resource constrained, smart micro-grids (RCSMG). A RCSMG loosely describes a micro-grid with distributed generators and demand controlled by selfish participants with limited information, power storage capacity and low literacy, communicate over an unreliable infrastructure burdened by limited bandwidth and low computational power of devices. In this thesis, we design and evaluate a CDA algorithm for power allocation in a RCSMG. Specifically, we offer the following contributions towards power auctioning on RCSMGs. First, we extend the original CDA scheme to enable decentralised auctioning. We do this by integrating a token-based, mutual-exclusion (MUTEX) distributive primitive, that ensures the CDA operates at a reasonably efficient time and message complexity of O(N) and O(logN) respectively, per critical section invocation (auction market execution). Our CDA algorithm scales better and avoids the single point of failure problem associated with centralised CDAs (which could be used to adversarially provoke a break-down of the grid marketing mechanism). In addition, the decentralised approach in our algorithm can help eliminate privacy and security concerns associated with centralised CDAs. Second, to handle CDA performance issues due to malfunctioning devices on an unreliable network (such as a lossy network), we extend our proposed CDA scheme to ensure robustness to failure. Using node redundancy, we modify the MUTEX protocol supporting our CDA algorithm to handle fail-stop and some Byzantine type faults of sites. This yields a time complexity of O(N), where N is number of cluster-head nodes; and message complexity of O((logN)+W) time, where W is the number of check-pointing messages. These results indicate that it is possible to add fault tolerance to a decentralised CDA, which guarantees continued participation in the auction while retaining reasonable performance overheads. In addition, we propose a decentralised consumption scheduling scheme that complements the auctioning scheme in guaranteeing successful power allocation within the RCSMG. Third, since grid participants are self-interested we must consider the issue of power theft that is provoked when participants cheat. We propose threat models centred on cheating attacks aimed at foiling the extended CDA scheme. More specifically, we focus on the Victim Strategy Downgrade; Collusion by Dynamic Strategy Change, Profiling with Market Prediction; and Strategy Manipulation cheating attacks, which are carried out by internal adversaries (auction participants). Internal adversaries are participants who want to get more benefits but have no interest in provoking a breakdown of the grid. However, their behaviour is dangerous because it could result in a breakdown of the grid. Fourth, to mitigate these cheating attacks, we propose an exception handling (EH) scheme, where sentinel agents use allocative efficiency and message overheads to detect and mitigate cheating forms. Sentinel agents are tasked to monitor trading agents to detect cheating and reprimand the misbehaving participant. Overall, message complexity expected in light demand is O(nLogN). The detection and resolution algorithm is expected to run in linear time complexity O(M). Overall, the main aim of our study is achieved by designing a resilient and cheating-free CDA algorithm that is scalable and performs well on resource constrained micro-grids. With the growing popularity of the CDA and its resource allocation applications, specifically to low resourced micro-grids, this thesis highlights further avenues for future research. First, we intend to extend the decentralised CDA algorithm to allow for participants’ mobile phones to connect (reconnect) at different shared smart meters. Such mobility should guarantee the desired CDA properties, the reliability and adequate security. Secondly, we seek to develop a simulation of the decentralised CDA based on the formal proofs presented in this thesis. Such a simulation platform can be used for future studies that involve decentralised CDAs. Third, we seek to find an optimal and efficient way in which the decentralised CDA and the scheduling algorithm can be integrated and deployed in a low resourced, smart micro-grid. Such an integration is important for system developers interested in exploiting the benefits of the two schemes while maintaining system efficiency. Forth, we aim to improve on the cheating detection and mitigation mechanism by developing an intrusion tolerance protocol. Such a scheme will allow continued auctioning in the presence of cheating attacks while incurring low performance overheads for applicability in a RCSMG.
2018-01-01T00:00:00ZModelling evolving clinical practice guidelines: a case of MalawiMsosa, Yamiko Josephhttp://repository.aust.edu.ng/xmlui/handle/11427/283882018-11-26T13:54:30Z2018-01-01T00:00:00ZModelling evolving clinical practice guidelines: a case of Malawi
Msosa, Yamiko Joseph
Electronic medical record (EMR) systems are increasingly being adopted in low- and middle-income countries. This provides an opportunity to support task-shifted health workers with guideline-based clinical decision support to improve the quality of healthcare delivery. However, the formalization of clinical practice guidelines (CPGs) into computer-interpretable guidelines (CIGs) for clinical decision support in such a setting is a very challenging task due to the evolving nature of CPGs and limited healthcare budgets. This study proposed that a CIG modelling language that considers CPG change requirements in their representation models could enable semi-automated support of CPG change operations thereby reducing the burden of maintaining CIGs.
Characteristics of CPG changes were investigated to elucidate CPG change requirements using CPG documents from Malawi where EMR systems are routinely used. Thereafter, a model-driven engineering approach was taken to design a CIG modelling framework that has a novel domain-specific modelling language called FCIG for the modelling of evolving CIGs. The CIG modelling framework was implemented using the Xtext framework. The national antiretroviral therapy EMR system for Malawi was extended into a prototype with FCIG support for experimentation. Further studies were conducted with CIG modellers. The evaluations were conducted to answer the following research questions: i) What are the CPG change requirements for modelling an evolving CIG? ii) Can a model-driven engineering approach adequately support the modelling of an evolving CIG? iii) What is the effect of modelling an evolving CIG using FCIG in comparison with the Health Level Seven (HL7) standard for modelling CIGs? Data was collected using questionnaires, logs and observations. The results indicated that finegrained components of a CPG are affected by CPG changes and that those components are not included explicitly in current executable CIG language models. The results also showed that by including explicit semantics for elements that are affected by CPG changes in a language model, smart-editing features for supporting CPG change operations can be enabled in a language-aware code editor. The results further showed that both experienced and CIG modellers perceived FCIG as highly usable. Furthermore, the results suggested that FCIG performs significantly better at CIG modelling tasks as compared to the HL7 standard, Arden Syntax.
This study provides empirical evidence that a model-driven engineering approach to clinical guideline formalization supports the authoring and maintenance of evolving CIGs to provide up-to-date clinical decision support in low- and middle-income countries.
2018-01-01T00:00:00ZAn Introduction to Ontology EngineeringKeet, C Mariahttp://repository.aust.edu.ng/xmlui/handle/11427/283122018-11-26T13:54:29Z2018-07-16T00:00:00ZAn Introduction to Ontology Engineering
Keet, C Maria
An Introduction to Ontology Engineering is a free online textbook that provides an overview of ontology engineering, including logics and automated reasoning, methods and methodologies, top-down ontology development with foundational ontologies, and bottom-up strategies with non-ontological resources. It has three further specialized topics: Ontology-Based Data Access, multilingual ontologies and CNLs, and advanced modeling with language extensions.
Each chapter contains review questions and exercises, and two sample assignments are included at the end. Answers are provided for a selection of the exercises.
The approach to ontology engineering and the textbook’s contents are aimed at advanced undergraduate and postgraduate levels in computer science, and the book is structured accordingly. It could fit a semester-long course, covering roughly one chapter per week.
2018-07-16T00:00:00ZUsability heuristics for fast crime data anonymization in resource-constrained contextsSakpere, Aderonke Busayohttp://repository.aust.edu.ng/xmlui/handle/11427/281572018-11-26T13:54:29Z2018-01-01T00:00:00ZUsability heuristics for fast crime data anonymization in resource-constrained contexts
Sakpere, Aderonke Busayo
This thesis considers the case of mobile crime-reporting systems that have emerged as an effective and efficient data collection method in low and middle-income countries. Analyzing the data, can be helpful in addressing crime. Since law enforcement agencies in resource-constrained context typically do not have the expertise to handle these tasks, a cost-effective strategy is to outsource the data analytics tasks to third-party service providers. However, because of the sensitivity of the data, it is expedient to consider the issue of privacy. More specifically, this thesis considers the issue of finding low-intensive computational solutions to protecting the data even from an "honest-but-curious" service provider, while at the same time generating datasets that can be queried efficiently and reliably. This thesis offers a three-pronged solution approach. Firstly, the creation of a mobile application to facilitate crime reporting in a usable, secure and privacy-preserving manner. The second step proposes a streaming data anonymization algorithm, which analyses reported data based on occurrence rate rather than at a preset time on a static repository. Finally, in the third step the concept of using privacy preferences in creating anonymized datasets was considered. By taking into account user preferences the efficiency of the anonymization process is improved upon, which is beneficial in enabling fast data anonymization. Results from the prototype implementation and usability tests indicate that having a usable and covet crime-reporting application encourages users to declare crime occurrences. Anonymizing streaming data contributes to faster crime resolution times, and user privacy preferences are helpful in relaxing privacy constraints, which makes for more usable data from the querying perspective. This research presents considerable evidence that the concept of a three-pronged solution to addressing the issue of anonymity during crime reporting in a resource-constrained environment is promising. This solution can further assist the law enforcement agencies to partner with third party in deriving useful crime pattern knowledge without infringing on users' privacy. In the future, this research can be extended to more than one low-income or middle-income countries.
2018-01-01T00:00:00Z