Recently cloud computing has offered attractive solutions for academic and research institutions due to several reasons. In this chapter, the authors present a study of how cloud computing can be used for research and teaching activities in higher educational and research institutions in developing countries. Instead of focusing on cloud computing offering for basic IT infrastructures used in daily work of these institutions, the authors concentrate on the use of cloud computing for satisfying ad hoc needs of computing resources in research and teaching activities. Thorough analyses of research and teaching activities, requirements for cloud computing, benefits of utilizing cloud computing, and adoption barriers for these activities are also included. The authors then present the selected challenges in tackling these barriers and discuss possible approaches for solving these challenges and report lessons learned and experiences in utilizing and developing cloud computing solutions for teaching and research activities in Vietnam.
we also introduce an extended model that integrates existing work in describing quality of data, data and service contract, data dependency, and Quality of Service (QoS). We present a mechanism to incorporate DEMODS into both new and existing DaaSes. Finally, a prototype of DEMODS has been developed to evaluate the effectiveness of the proposed model.
This article introduces a dynamic cloud-based marketplace of near-realtime human sensing data (MARSA) for different stakeholders to sell and buy near-realtime data. MARSA is designed for environments where information technology (IT) infrastructures are not well developed but the need to gather and sell near-realtime data is great. To this end, we present techniques for selecting data types and managing data contracts based on different cost models, quality of data, and data rights. We design our MARSA platform by leveraging different data transferring solutions to enable an open and scalable communication mechanism between sellers (data providers) and buyers (data consumers). To evaluate MARSA, we carry out several experiments with the near-realtime transportation data provided by people in Ho Chi Minh City, Vietnam, and simulated scenarios in multicloud environments.
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