Cloud services, interoperability and analytics within a ROLE-enabled personal learning environment

The ROLE project (Responsive Open Learning Environments, EU 7th Framework Programme, grant agreement no.: 231396, 2009-2013) was focused on the next generation of Personal Learning Environments (PLEs). A ROLE PLE is a bundle of interoperating widgets - often realised as cloud services - used for teaching and learning. In this paper, we first describe the creation of new ROLE widgets and widget bundles at Galileo University, Guatemala, within a cloud-based infrastructure. We introduce an initial architecture for cloud interoperability services including the means for collecting interaction data as needed for learning analytics. Furthermore, we describe the newly implemented widgets, namely a social networking tool, a mind-mapping tool and an online document editor, as well as the modification of existing widgets. The newly created and modified widgets have been combined in two different bundles that have been evaluated in two web-based courses at Galileo University, with participants from three different Latin-American countries. We measured emotional aspects, motivation, usability and attitudes towards the environment. The results demonstrated the readiness of cloud-based education solutions, and how ROLE can bring together such an environment from a PLE perspective

Towards a framework for predicting whole life-cycle cost for long-term digital preservation

Estimating the costs for the whole lifecycle of long-term digital preservation (LTDP) activities ena-bles decision makers to choose carefully what data to preserve, duration of preservation and type of preservation techniques best applied for their information. To address this need, a framework is de-veloped to generate a cost model that will estimate costs for long-term digital preservation activities using storage in the cloud and taking into consideration the impact of mitigating uncertainties, espe-cially obsolescence issues on future costs. This cost estimating framework is part of the European pro-ject entitled ‘Enabling kNowledge Sustainability Usability and Recovery for Economic value’ which aims to provide a total long-term digital preservation solution for companies and public sector organi-sations interested in keeping their digital information alive for the long-term within the healthcare, fi-nancial and the clinical trials business sectors

Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

Toward a framework for data quality in cloud-based health information system

This Cloud computing is a promising platform for health information systems in order to reduce costs and improve accessibility. Cloud computing represents a shift away from computing being purchased as a product to be a service delivered over the Internet to customers. Cloud computing paradigm is becoming one of the popular IT infrastructures for facilitating Electronic Health Record (EHR) integration and sharing. EHR is defined as a repository of patient data in digital form. This record is stored and exchanged securely and accessible by different levels of authorized users. Its key purpose is to support the continuity of care, and allow the exchange and integration of medical information for a patient. However, this would not be achieved without ensuring the quality of data populated in the healthcare clouds as the data quality can have a great impact on the overall effectiveness of any system. The assurance of the quality of data used in healthcare systems is a pressing need to help the continuity and quality of care. Identification of data quality dimensions in healthcare clouds is a challenging issue as data quality of cloud-based health information systems arise some issues such as the appropriateness of use, and provenance. Some research proposed frameworks of the data quality dimensions without taking into consideration the nature of cloud-based healthcare systems. In this paper, we proposed an initial framework that fits the data quality attributes. This framework reflects the main elements of the cloud-based healthcare systems and the functionality of EHR

HPC Cloud for Scientific and Business Applications: Taxonomy, Vision, and Research Challenges

High Performance Computing (HPC) clouds are becoming an alternative to on-premise clusters for executing scientific applications and business analytics services. Most research efforts in HPC cloud aim to understand the cost-benefit of moving resource-intensive applications from on-premise environments to public cloud platforms. Industry trends show hybrid environments are the natural path to get the best of the on-premise and cloud resources---steady (and sensitive) workloads can run on on-premise resources and peak demand can leverage remote resources in a pay-as-you-go manner. Nevertheless, there are plenty of questions to be answered in HPC cloud, which range from how to extract the best performance of an unknown underlying platform to what services are essential to make its usage easier. Moreover, the discussion on the right pricing and contractual models to fit small and large users is relevant for the sustainability of HPC clouds. This paper brings a survey and taxonomy of efforts in HPC cloud and a vision on what we believe is ahead of us, including a set of research challenges that, once tackled, can help advance businesses and scientific discoveries. This becomes particularly relevant due to the fast increasing wave of new HPC applications coming from big data and artificial intelligence.Comment: 29 pages, 5 figures, Published in ACM Computing Surveys (CSUR

CloudSim Express: A Novel Framework for Rapid Low Code Simulation of Cloud Computing Environments

Cloud computing environment simulators enable cost-effective experimentation of novel infrastructure designs and management approaches by avoiding significant costs incurred from repetitive deployments in real Cloud platforms. However, widely used Cloud environment simulators compromise on usability due to complexities in design and configuration, along with the added overhead of programming language expertise. Existing approaches attempting to reduce this overhead, such as script-based simulators and Graphical User Interface (GUI) based simulators, often compromise on the extensibility of the simulator. Simulator extensibility allows for customization at a fine-grained level, thus reducing it significantly affects flexibility in creating simulations. To address these challenges, we propose an architectural framework to enable human-readable script-based simulations in existing Cloud environment simulators while minimizing the impact on simulator extensibility. We implement the proposed framework for the widely used Cloud environment simulator, the CloudSim toolkit, and compare it against state-of-the-art baselines using a practical use case. The resulting framework, called CloudSim Express, achieves extensible simulations while surpassing baselines with over a 71.43% reduction in code complexity and an 89.42% reduction in lines of code

Secure multi-party computation for analytics deployed as a lightweight web application

We describe the definition, design, implementation, and deployment of a secure multi-party computation protocol and web application. The protocol and application allow groups of cooperating parties with minimal expertise and no specialized resources to compute basic statistical analytics on their collective data sets without revealing the contributions of individual participants. The application was developed specifically to support a Boston Women’s Workforce Council (BWWC) study of wage disparities within employer organizations in the Greater Boston Area. The application has been deployed successfully to support two data collection sessions (in 2015 and in 2016) to obtain data pertaining to compensation levels across genders and demographics. Our experience provides insights into the particular security and usability requirements (and tradeoffs) a successful “MPC-as-a-service” platform design and implementation must negotiate.We would like to acknowledge all the members of the Boston Women’s Workforce Council, and to thank in particular MaryRose Mazzola, Christina M. Knowles, and Katie A. Johnston, who led the efforts to organize participants and deploy the protocol as part of the 100% Talent: The Boston Women’s Compact [31], [32] data collections. We also thank the Boston University Initiative on Cities (IOC), and in particular Executive Director Katherine Lusk, who brought this potential application of secure multi-party computation to our attention. The BWWC, the IOC, and several sponsors contributed funding to complete this work. Support was also provided in part by Smart-city Cloud-based Open Platform and Ecosystem (SCOPE), an NSF Division of Industrial Innovation and Partnerships PFI:BIC project under award #1430145, and by Modular Approach to Cloud Security (MACS), an NSF CISE CNS SaTC Frontier project under award #1414119