https://www.um.edu.mt/library/oar/handle/123456789/5626 Thu, 23 Apr 2026 13:44:04 GMT 2026-04-23T13:44:04Z https://www.um.edu.mt/library/oar/handle/123456789/145526 Title: Unified load balancing strategies for enhanced cloud computing solutions Abstract: Cloud computing offers scalable, on-demand resources that enable a variety of services and applications. Effective load balancing in cloud environments is essential for maintaining performance and Quality of Service (QoS). These environments present complex, dynamic conditions that make efficient load balancing challenging. Many existing algorithms focus on single-objective optimisation, such as minimising response time, which often results in trade-offs and inefficiencies when dealing with unpredictable workloads. This dissertation tackles these inefficiencies by introducing a unified, multi-objective load balancing strategy that combines Ant Colony Optimisation (ACO) and Genetic Algorithm (GA) techniques. The hybrid ACO-GA algorithm is implemented within the CloudAnalyst simulation environment, leveraging ACO’s rapid local search and GA’s global exploration capabilities to dynamically balance workloads across cloud resources. Extensive simulation experiments demonstrate that the proposed hybrid approach significantly improves key QoS metrics compared to both conventional and state-of-the-art load balancers. The ACO-GA consistently achieved substantially lower average response times and improved load distribution relative to traditional algorithms. For example, under light workloads it reduced mean response time by roughly 50% versus Round Robin and 40% under heavy loads. The hybrid method also outperformed modern heuristics, sustaining about 8–10% faster response than advanced metaheuristic policies while shortening data centre processing delays. These gains were accompanied by more efficient resource utilisation, as the algorithm prevented server overloading and underutilisation through balanced task allocation. Notably, performance improvements persisted across both low and high demand scenarios, highlighting the algorithm’s robust adaptability to dynamic cloud conditions. Overall, the results affirm that this unified ACO-GA strategy effectively addresses the limitations of single-objective approaches, offering a significant enhancement in cloud service performance, resource utilisation and QoS. Description: M.Sc. ICT(Melit.) Wed, 01 Jan 2025 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/145526 2025-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/144337 Title: A framework to support test tool design and acquisition Abstract: Software testing is an important facet of software delivery, supported by tools intended to improve the efficiency and effectiveness of testing. Industry experience and academic research show that tool adoption can be problematic; tools are acquired but not used, or are used but do not deliver. The research problem this thesis addresses is how to design tools that better match the needs of testers to operate in an increasingly complex socio‐technical environment. Industry practitioners’ and experts’ experiences with tools were explored, through in‐depth interviews, workshops and surveys. It was found that testers experienced frustrations arising from tools which, while offering attractive interfaces, did not provide quality in use necessary to meet testers’ needs. In this work, this is referred to as the ‘illusion of usability’. This illusion arises from a superficial understanding of usability as being focused on the user interface, working with a limited persona set, and focusing narrowly on usability, without considering the other attributes that make up quality in use. Furthermore, finding that testers do not conform to the stereotype of IT workers, and cannot be represented in tool design by a simple, small set of personas or archetypes, it was decided to apply an HCI lens to the problem, with the research question “How can HCI techniques help with the design of test tools?” In answering this question, this work proposes an empirically grounded framework (idea‐t), which supports decision making in both design and acquisition of tools through a set of heuristics, guidelines and activities. The idea‐t framework (“Influencing the Design, Evaluation and Acquisition of Tools for Testing”) emerged following a series of studies and was iteratively reviewed and validated through five industry case studies. Learning was carried forward from each case study and applied to the framework. The five formative case studies iteratively informed the development of the framework, while also providing evidence of its effectiveness in the process. Participants reported benefits including new insights and improved communication within their teams. A final retrospective analysis evaluated the framework by examining a backlog of customer issues raised on a commercial tool; it was found that potentially 40% of issues could have been mitigated by the idea‐t framework. Expert reviews were also carried out to assess the latest version of the framework, where experts from testing, test tool development, and HCI provided positive feedback on the framework’s efficacy, and suggestions for its practical application. Description: Ph.D.(Melit.) Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/144337 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/143231 Title: Design and performance evaluation of a green LED OFDM LiFi system for an electromagnetic interference sensitive hospital network Authors: Sharma, Ajay; Garg, Lalit; Atieh, Ahmad; Xuereb, Peter A. Abstract: Light Fidelity (LiFi) is an alternative technology to Wireless Fidelity (WiFi) for secure, high-speed hospital communication. The main objective of this study is to design a Four-Quadrature Amplitude Modulation-Orthogonal Frequency Division Multiplexing (4QAM-OFDM) LiFi system that overcomes electromagnetic interference (EMI), ensures biological safety, guarantees secure medical data transmission, and delivers high-speed, low-latency connectivity for hospital networks. The core contribution is a holistic 4QAM-OFDM LiFi design that offers superior spectral efficiency, significantly reduced Bit Error Rate (BER), and compliance with healthcare safety standards compared to existing LiFi systems, as demonstrated by its simulation using OptiSystem 21 and MATLAB R2024b. Using a 500 nm Light-Emitting Diode (LED) compliant with photobiological safety standards safeguards biological safety, while utilizing 1024-subcarrier OFDM decreases ISI. The receiver’s Positive-Intrinsic-Negative (PIN) photodetector converts optical signals to electrical form, while the quadrature demodulator minimizes phase distortion, achieving a BER of 4.25E-3 at 30 dBm— further reducible to E-9 with error correction for reliable hospital communication. This performance demonstrates the system’s suitability for mission-critical applications such as AI-assisted diagnostics, robotic surgery, and real-time medical imaging. The proposed system maintained excellent tolerance to both multipath distortion and external EMI, resolving EMI-related device interference, improving energy efficiency through reduced power consumption, and enhancing security via optical confinement that prevents signal leakage beyond hospital rooms. This enables a practical and scalable pathway for replacing WiFi in hospital environments, ensuring uninterrupted, high-speed, and safe communication for both routine and life-critical healthcare applications. The system reduces power consumption, diminishes CO₂ emissions, and improves hospital energy efficiency by promoting sustainable and eco-friendly LiFi technology. This study confirms LiFi as a secure, high-performance WiFi alternative for hospitals, meeting healthcare standards. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/143231 2026-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/143061 Title: Itinerary planning in wireless sensor networks using fuzzy logic and particle swarm optimization Authors: K, Lingaraj; Malghan, Rashmi; Rao, Karthik; Garg, Lalit; H. M., Vishwanatha; Madhavi J, Bindu Abstract: Wireless sensor networks (WSNs) can benefit from mobile agent technology in several ways, including decreased network traffic and energy-efficient data collection techniques. Path scheduling for mobile agents (MAs) is currently a crucial component of WSNs. However, routing all MAs across WSNs must be carefully organized to reduce resource costs and increase information accuracy. Numerous studies have developed routing algorithms for installing several MAs in a particular network. They planned routes, so the mobile agent checks pursued distinct paths to gather information from the nodes efficiently. This paper presents a novel fuzzy logic-based particle swarm optimization itinerary planning technique (FLPSO). The FLPSO employs techniques associated with the fuzzy logic model (FLM) and classifies the sensor into distinct types depending on the paths specified by the mobile agent trips. Mobile agents adhere to hybrid planning determined by particle swarm optimization (PSO) planning and gather data only from authorized groups. The experimental results illustrate the efficacy and superiority of the proposed method over current methods, concerning 10% better energy consumption and 15% better task delay (time). Description: Electronic supplementary material is attached. Thu, 01 Jan 2026 00:00:00 GMT https://www.um.edu.mt/library/oar/handle/123456789/143061 2026-01-01T00:00:00Z