A pinboard by
Mugyenyi Raymond

Doctorate Candidate, Atlantic International University/School of Engineering and Technology



Commercial banks in Uganda have been realised to be continuously increasing in number of branches, sizes and operational activities in the last two decades. This increment has attracted high operational costs related to purchase and maintenance of IT infrastructure and even requiring larger spaces to accommodate them, which is always accompanied by poor data storage and management. Cloud computing is identified as the best and latest solution to curb the problems in commercial banks, if adopted. Cloud computing has the capacity to store and manage data on virtualized servers so that, applications, individuals and organizations around the world can have the ability to connect to data and computing resources anywhere and anytime which improves the reliability since the data and application are stored and backed up on a number of computers which reduces the chance of data and application loss. This paper aimed at studying the benefits of cloud computing to commercial institutions and how the services can be adopted by the institutions of Uganda so as to successfully overcome the continuous expanding challenges that are always reported. A proposed system for cloud computing deployment to serve commercial banks has been developed together with recommendations for cloud computing adoption and effective utilization and management. The relevant conclusions for the paper have also been drawn.


Big Data Processing for Renewable Energy Telemetry Using a Decentralized Cloud M2M System

Abstract: Hydro-, Aeolian and Solar energy show significant promise in helping to reduce pollutants and greenhouse gases, which is a primary focus in today’s sustainable development culture. To enjoy the power of them, the human society needs solutions to transform the energies mentioned above into electric energy, at specific reliability, efficiency and sustainability parameters. Maintaining this kind of parameters implies, among other things, the careful and permanent monitoring of equipment. The monitoring process implies remote monitoring, as we are talking about preserving natural resources. The equipment is mostly situated in the middle of nature, covering large areas mostly outside of populated locations. In their great majority installations for wind and solar energy have been designed and manufactured relatively recently, which makes them contain systems of tele-monitoring that are designed and included by default, as a part of great importance to the entire investment. The situation is different in the case of hydroelectric plants, which have a tradition of over 130 years and have been and are still built to this day. Renewable energy sources are being increasingly used and need to be constantly monitored for optimizing the power grid. Unfortunately, such micro power plants are located in difficult to access remote locations where often only satellite or sparse GSM radio signals are available. In this paper we study the way how to process big data gathered by a decentralized cloud system, based on general systems and remote telemetry units (RTUs), for tele-monitoring of renewable energy objectives. Also, we analyze a proposed cloud M2M system, where each RTU communicates by radio with a telemetry data gateway connected to a cloud computing infrastructure equipped with appropriate software that delivers processed data. Furthermore, we present how we use a search based application built on Exalead CloudView to search for weak signals in big data. In particular, given the telemetry application, we propose to leverage trivial and non-trivial connections between different sensor signals and data from other online environmental wireless sensor networks, in order to find patterns that are likely to provide innovative solutions to existing problems. The aggregation of such weak signals will provide evidence of connections between renewable energies and environmental related issues faster and better than trivial mining of sensor data. As a consequence, the software has a significant potential for matching environmental applications and challenges that are related in non-obvious ways. Finally, we present the measurement results for a hydro-energy case study and discuss the applicability for other renewable sources such as solar or wind energy.

Pub.: 19 Apr '15, Pinned: 05 Sep '17

Cloud-based design for disassembly to create environmentally friendly products

Abstract: To date, environmental awareness and government regulations have made businesses more responsible for waste disposal. From the product development standpoint, particularly in the design phase, disassembly factors including component disassemblability and recyclable component classification require further investigation. There has, however, been little literature survey focusing on disassemblability enhancement at the product design stage with the disassembly guidelines. In addition, cloud computing enables many applications of Web services and rekindles the interest of providing design services via the Internet. Recent research indicates that design delivered through cloud computing will outperform the traditional IT offers. In this study, the proposed methodology provides an total solution, which is able to: (1) Model the relationship of components and modularity, (2) explore component disassemblability and identify modules, (3) recognize disassembly patterns, (4) provide disassembly guidelines and recyclable component classification to instruct how to disassemble components, and (5) based on a cloud computing architecture, designers exchange and store their design information and knowledge for new sustainable product development. A case in electronic industry is studied and the results show that these companies are brought into conformance with environmental regulations, thereby enhancing product reuse, reduce, recycle, and reducing the disassembly time.

Pub.: 21 May '15, Pinned: 05 Sep '17

A Green Private Cloud Architecture with global collaboration

Abstract: Energy-saving and environmental protection have become the most popular and important research topics at present. Green Computing, as an indispensable part, is a new computing model to promote scientific progress and sustainable social development. It has become the focus and the high ground of international competition, relating to the country’s political, economic and social security. In this paper, from the point of view reducing server redundancy and improving PC terminal performance, heterogeneous systems are deployed in a few or even a single server by using the virtualization technology. A globally collaborative mechanism of the Green Private Cloud Computing (GCMGPC) is proposed and the Green Private Cloud Architecture model is built with virtualization technology for meliorating the status. It can change the reality that the operating environment of Cloud Computing relies on backend servers excessively. Meanwhile, it provides a cooperative method of workload balance between servers and clients through a resources sharing dynamically balancing algorithm with the cloud servers and clients (RSDBASC). It can meet the requirement that transforms the clients into the similar cloud server nodes (SCSNs) under the premise of not increasing the number of the servers. The new integrated Green Private Cloud Architecture with global collaboration can greatly improve the utilization of hardware resources and allocate the global resource more rationally. By this architecture, it will achieve three purposes, including energy-saving, expenditure-reducing and efficiency. Experiments are carried out to validate the feasibility and superiority by such model, and the results are shown great. The presented methods establish a favorable foundation for the future research of Green Public Cloud.

Pub.: 27 Oct '11, Pinned: 05 Sep '17