Faculty of Science, Agriculture and Engineering

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Browsing Faculty of Science, Agriculture and Engineering by Author "Adigun, M.O"

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    Database-as-a-service integration with ad hoc mobile cloud-powered GUISET
    (University of Zululand, 2017) Fakude, Siphelele C.; Mba, I.N; Adigun, M.O
    The World Wide Web has advanced considerably in the recent years. These advancements have also been expanded to the mobile environments, where mobile devices are now capable of doing most of the operations that were initially intended for traditional computers. Due to the resource poverty situation facing mobile devices, i.e., mobile devices having limited storage capacity, processing and battery power, these advanced capabilities come at a cost. Because of this challenge, computing paradigms such as Mobile Cloud Computing (MCC) have been introduced in an attempt to mitigate this challenge. With MCC, most of the processing and storage is moved from the mobile device to the cloud server, thus conserving the device’s resources. For this to be realisable, the presence of an Internet link between the mobile device and the cloud is required. However, due to the fluctuation of wireless links, the always-on Internet connectivity between the cloud and mobile devices is not achievable at all times. The Internet disconnections result in cloud resources being unreachable by the mobile users, which has a negative impact on most applications. In an attempt to mitigate the connectivity outage issue between mobile devices and the cloud, this work proposes the usage of a cache to maintain data availability to mobile clients who were initially using the DBaaS model to store their data. The proposed cache model is used only during Internet disconnections, and uses a prefetching mechanism to periodically retrieve its data from the central cloud. The usability of this model applies in Ad hoc Mobile Clouds (AMC), where a group of disconnected mobile devices collaborate to form a community cloud. Furthermore, the integration of an AMC with the Grid-based Utility Infrastructure for SMME Enabling Technology (GUISET) to achieve smooth running of offline clients is proposed. This work further develops a prototype of the model, and the evaluation results show that our model performs better in terms of maintaining data availability to occasionally disconnected clients.
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    Development of a cloud based privacy monitoring framework for the health sector
    (University of Zululand, 2014) Shabalala, M.V; Tarwireyi, P; Adigun, M.O
    Cloud computing is growing in popularity due to its ability to offer dynamically scalable resources provisioned as services regardless of user or location device. However, moving data to the cloud means that the control of the data is more in the hands of the cloud provider rather than the data owner. This is a great challenge that continues to hinder cloud computing from successfully achieving its potential. This is due to the fact that with cloud computing, the storage and processing of private information is done on remote machines that are not owned or even managed by the cloud consumers. This brings about significant security and data privacy concerns that impede the broader adoption of cloud computing, which compromises the vision of cloud computing as a new IT procurement model. In an attempt to address the aforementioned challenge, a privacy monitoring framework for the cloud computing environment was developed in this work. The design science methodology for information system was followed. The framework was evaluated using an experimental method. The evaluation of the framework mainly focused on the metrics that evaluate the satisfaction of the users’ goals. The quantitative evaluation aspect entailed the usability test and questionnaires to get results. From questionnaires the statistical data was found and analyzed. The results reported in this study show that the developed privacy monitoring framework could help cloud customers monitor the privacy of their personally identifiable information in the cloud. The framework employs the developed informative event and access logs analyser which enables customers to track and comprehend how their data is handled in the cloud.
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    A QoS-Aware Web Service Client Framework for GUISET
    (University of Zululand, 2011) Mathonsi, E.L; Adigun, M.O
    Web Services have become one of promising technologies, and is getting widely adopted in business and also gradually deployed in real customer environment. The technology of Web Service is capable of providing a means to integrate different functional components over the Internet and enabling business entities to interact with one another through standard application program. As more and more Web Services become available on the service registry, selecting one Web Service among a group of Web Services which are offering similar functionality is a challenge. Quality of Service (QoS) is becoming an important criterion for differentiating Web services that offer similar functionality. However, the current SOA environment does not support QoS. This is because the discovery mechanism of the current SOA environment only considers the functionality (what the Web service does) of a Web service. There are many research efforts that attempted to address these issues in QoS-aware service discovery and selection but they still leave a lot to be desired. In this research work we propose an approach that utilises both the functionality and the QoS information of a Web service during service discovery and selection. This is realizable through our proposed GUISET QoS-aware Web service Selection Broker (G-Broker). The G-Broker allows service consumers to express their QoS requirements and select the most appropriate Web service for the service consumer. It also measures the QoS information of the selected Web service to avoid false QoS guarantees. It provides support for QoS negotiation between service consumer and providers and forces Service Level Agreement (SLA) creation. Lastly, it allows monitoring of the agreed QoS between clients and providers, and therefore, detecting any QoS violation. The G-Broker provides more satisfaction to consumers and also scales well as the number of Web services published in the service registry increases.
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    QoS-Based Web Service Selection Mechanism for Ad-hoc Mobile Cloud Computing
    (University of Zululand, 2017) Akinola, Ayotuyi Tosin; Adigun, M.O; Xulu, S.S
    The Ad-hoc Mobile Cloud Computing (AMC) paradigm came into existence to settle one of the major challenges of Mobile Cloud computing especially low internet connectivity. The AMC is formed when mobile devices in the same proximity connect through a wireless connection or any other means; enabling the devices to request web services from one another within the Mobile Cloud. However, the user dissatisfaction experienced in the course of requesting for a Web Service is a challenge that needs to be addressed. This is because existing service selection approaches emphasized functional rather than non-functional qualities of matched services. Moreover, effective selection approaches must avoid quality computation during service selection that produces similar or redundant results at runtime. In an attempt to address this service selection challenge, a service selection mechanism for Ad-hoc Mobile Cloud was developed in this work. This mechanism was synthesized from existing service selection approaches. The mechanism was evaluated using the experimental research method. The evaluation of the mechanism accesses the suitability of the selected web services for all requesting users. The quantitative evaluation aspect entails the use of execution time, throughput and service availability to analyse the performance of the selection approach. The approach employs the use of selected Quality of Service (QoS) properties and user feedback to determine the most appropriate service to be selected for any request. Experiments affirm a continuous updated and unlimited range of users’ Web Service assessment (Feedback) as part of QoS properties enhances more optimal service selection within AMC computing paradigm. The is because non- feedback enabled attains one optimal selection out of seven thus guaranteeing 0.13 probability of optimal selection against a probability of 1 depicted in feedback-based selection mechanism.
University of Zululand