Cloud computing is a standard that is fast gaining momentum in the IT world. The availability of storage capacity that can be accessed and increased as the need arises makes computing easier. Applications can also be deployed using services provided by a cloud service provider. Portability allows utilization of applications and services across various domains. Portability could be in the area of programming language, application programming interface, data storage or data migration. Clearly, the easier it is to move services across various providers, the more attractive cloud computing becomes. The study was executed by means of review of some literature available on cloud application portability. This chapter examines current trends in cloud application portability area and gives focus for future research. In the present work, the objective is to answer the following question: what is the current trend and development in cloud application portability? Papers published in journals, conferences, white papers, and reputable magazines were analyzed. Some core topic facets were used in this review for the identification of trends in cloud application portability. The finding is that discussions on virtualization and API-specific issues are not adequate. This will be of benefit to prospective cloud users and even cloud providers.
The development of any country is closely related to its ability to provide access to electricity for productive labor. Many countries in sub-Saharan Africa have low electrification rates for commercial, industrial and residential consumers. This study focuses on Nigeria, which has one of the largest populations and economies in sub-Saharan Africa. Although Nigeria possesses abundant renewable energy resources that can increase electricity generation, it has suffered a significant setback in electricity generation. However, for Nigeria to become one of the leading industrialized countries by 2030, access to clean, reliable, and sustainable energy sources is vital (Vision 20: 2030). This study assesses the possibility of Nigeria developing and transitioning to the use of various energy sources. Additionally, this study evaluates greenhouse gas (GHG) mitigation plans and future trends in energy sustainability through multi-criteria decision analysis (MCDA), considering the technical, social, economic, and environmental dimensions of the sustainability structure. A total of twelve (12) sustainability indexes were taken into consideration; these consist of two (2) technical, three (3) social, three (3) environmental, and four (4) economic indicators. A scenario-based software called Long-range Energy Alternative Plan (LEAP) was used to integrate the analysis criteria and forecast a sustainable energy generation mix for the future. It considered three scenarios, namely: the business as usual scenario (BAU); renewables, natural gas and biomass scenario (RNB); and renewables and coal scenario (REC). It was concluded that the renewables, natural gas, and biomass scenario (RNB) is the best scenario to solve Nigeria’s energy problem based on the aim of the study.
The burning of fossil fuel for power generation emits Greenhouse gases into the environment. Greenhouse Gases (GHGs) emission is the principal cause of global warming. In order to regulate the emissions of these gases, the emissions need to be assessed and quantified. Carbon footprint is the evaluation of human activities that lead to GHGs emissions. The Covenant University Electricity Network during periods when utility supply fail runs on diesel powered generators located at different centers within the campus. These generators emit carbon-based compounds into the environment. Assessing the quantity of carbon dioxide which is the principal GHGs emitted per year gives 33.14-tonnes. Analysis of the load profiles in the centers showed that all the eight generators are not supposed to be running simultaneously as it is now. This study developed a new network model where all the generators were integrated into a DC microgrid that ensured resource sharing. The model was simulated using energy management and optimization techniques resulting in reduced micro-generators engagement, Green House Gases emission and fuel consumption. Consequently, carbon dioxide emitted per year dropped to 18.44-tonnes from 33.14-tonnes. The developed model improved the carbon footprint of the campus by as much as 44.3%.
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