/library/oar/handle/123456789/14102 Wed, 24 Dec 2025 13:30:10 GMT 2025-12-24T13:30:10Z /library/oar/handle/123456789/135067 Title: Causal consistency through a novel distributed middleware over strongly consistent transaction processing Abstract: Our research deals with the concept of causal consistency of data in the context of transactional information systems with scalability and high availability require- ments. We deal with the consistency of data which is stored and replicated in multiple physical locations. Given the data store’s distributed nature, a new set of data inconsistency issues arise. These cause clients to get an inconsistent, and therefore possibly incorrect, view of the data, yielding application errors and even susceptibility to security vulnerabilities. Most problems do not impact centralised databases, but centralised databases do not provide the resiliency and performance characteristics required by modern enterprise transactional information systems. We focus on this set of data inconsistency problems, and propose solutions to strengthen consistency guarantees without jeopardising the benefits of a distributed database. We model causal consistency, the strongest type of consistency that can be implemented in fault-tolerant, scalable databases, using the Actor model of com- putation. The model is then implemented on top of commercially-ready relational database management systems that are built to provide strong consistency. Data Inconsistency, Transaction Inconsistency and Integrity Invariant Violation are three related, but distinct, problems tackled in this research. For each prob- lem, we review the literature as well as design, implement and evaluate a novel solution. Our work shows that it is possible to have a distributed middleware that implements causal consistency with transaction consistency and integrity invariant preservation over a set of disconnected relational databases deployed within geo- graphically distributed data centres. Thus, our approach addresses each problem whilst answering to the scalability and resiliency needs of modern systems. Empirical results show that our middleware achieves better performance when compared to a single-node (i.e., non-distributed) relational database management system. We also extend our solution for Data Inconsistency and deploy the middle- ware on many machines within a data centre. In doing so, we identify and propose solutions for the complexities that arise from scaling the middleware horizontally, whilst our benchmarks show a significant increase in the amount of operations that can be processed at each data centre, and that data changes are replicated across geographically distributed instances of the system within acceptable timeframes. Description: Ph.D.(Melit.) Sun, 01 Jan 2023 00:00:00 GMT /library/oar/handle/123456789/135067 2023-01-01T00:00:00Z /library/oar/handle/123456789/129597 Title: A blockchain-based framework and process guide for intelligent exchange and use of health information in low resource environments Abstract: Enterprise software systems integration can be simple or complicated depending on the number of components and predictability of component interactions. Designing enterprise software systems with many adaptive components that learn as they interact is not easy. Software systems are often designed as function-specific systems that mimic user concerns modeled around organizational structure and communication patterns. Even a single and simple enterprise now has multiple integrated applications. Traditional integration styles are file sharing, shared databases, remote procedure calls, and messaging. These traditional approaches often require a trusted and centralized access-issuing database owner for multi-stakeholder enterprise systems. In the last decade, a new trustless software integration pattern has been facilitated by blockchain. Enterprise blockchain frameworks have been developed, yet practical use cases are few. Use cases still require domain data standardization, token modeling, and interface for regulatory intervention while preserving participants' privacy. This Thesis investigates enterprise integration using the Health ¸£ÀûÔÚÏßÃâ·Ñ Exchange (HIE) use case whose value proposition to healthcare stakeholders is well established. Governments, software vendors, non-profits, and private players traditionally perform the central HIE intermediation role. These intermediation efforts faced many bottlenecks. One main challenge is exchanging large numbers of structured, unstructured, and standardized datasets and terminology sets. This complexity has, over the years, resulted in many healthcare data standards. Description: Ph.D.(Melit.) Mon, 01 Jan 2024 00:00:00 GMT /library/oar/handle/123456789/129597 2024-01-01T00:00:00Z /library/oar/handle/123456789/124735 Title: Data security in cloud-centric multi-tenant databases Abstract: Cloud computing has swiftly gained momentum in the technological industry, owing to its numerous benefits, notably its ability to scale, ensure availability, and lower expenses. Countless organisations have transitioned their operations to the cloud, and it is anticipated that nearly all businesses will rely on cloud-based systems in the forth-coming years. Cloud computing has initiated significant transformations, particularly in the realm of Software as a Service (SaaS), where conventional database management systems (DBMSs) have evolved into Cloud-DBMSs (CDBMSs). Alongside this transition and within the same domain, there has been a shift from conventional single tenant database systems towards multi-tenant architectures that facilitate efficient sharing of the underlying infrastructure and resources. Despite the prior-mentioned advantages, organisations continue to exhibit hesitancy in adopting multi-tenant database systems particularly due to concerns regarding data security. The prospect of storing data from multiple tenants on the same server, or potentially within the same database tables, amplifies apprehensions of unauthorised access. Within this context, the focus of this dissertation revolves around the domain of cloud-centric database security, with particular focus on the unique intricacies presented by multi-tenant architectures. The aim is that of creating an automated process that aids software houses and database administrators in implementing security assertions for multi-tenant database systems prior to storing data online. This automation, in the form of a Computer-Aided Software Engineering (CASE) tool, enables the generation of tenant-specific secure database profiles, taking into account prevalent threats in CDBMSs and a comprehensive list of security requirements. A relational data model and SQL scripts are utilised as the main basis of this thesis whilst database design diagrams ensure that security is inbuilt from the initial stages of database design. Conclusively, a comprehensive analysis conducted on the proposed tool across various dimensions, including system coverage, performance, and security, demonstrates its successful attainment of the objectives established prior to its development. Description: Ph.D.(Melit.) Mon, 01 Jan 2024 00:00:00 GMT /library/oar/handle/123456789/124735 2024-01-01T00:00:00Z /library/oar/handle/123456789/122825 Title: SADIP : semi-automated data integration system for protein databases Abstract: Biologists must commonly combine information from different biological databases, by manually following cross-references (hyperlinks), using the distinct access methods and data formats provided by the databases. Past research in data integration has outlined several approaches which can integrate biological databases to provide a unified view. One approach is known as data warehousing. The current state of the art in biological data warehousing, requires bespoke software development and maintenance for each database. In our view, this is infeasible given the large number of constantly changing biological databases with varying access methods and data formats. This project aims to develop a tool which can automatically integrate biological information from different databases into a data warehouse, using user-defined configurations. This tool was applied to construct a property graph database with integrated information from 10 protein databases. This allows bioinformaticians to specify complex queries through the Standard Query Language (SQL). On top of this, a web-based user interface was developed which provides biologists with all integrated information related to a single protein identified by a UniProtKB identifier. The obtained results for the utilised configuration show that developing such a tool is feasible. However, the developed prototype requires further amendments to improve its flexibility, robustness, and security. Further results obtained show that the data warehouse provides biologists with a considerable amount of valuable information but should be extended to incorporate a wider variety of biological information. Finally, the results highlighted performance deficiencies for nested information and structural domains. Description: B.Sc. IT (Hons)(Melit.) Sat, 01 Jan 2022 00:00:00 GMT /library/oar/handle/123456789/122825 2022-01-01T00:00:00Z