Silvia Cristina Sardela Bianchi

Big Data computing and clouds

This paper discusses approaches and environments for carrying out analytics on Clouds for Big Data applications. It revolves around four important areas of analytics and Big Data, namely (i) data management and supporting architectures; (ii) model development and scoring; (iii) visualisation and user interaction; and (iv) business models. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions. Survey of solutions for carrying out analytics and Big Data on Clouds.Identification of gaps in technology for Cloud-based analytics.Recommendations of research directions for Cloud-based analytics and Big Data.

Context-Aware Job Scheduling for Cloud Computing Environments

The more instrumented society is demanding smarter services to help coordinate daily activities and exceptional situations. Applications become sophisticated and context-aware as the pervasiveness of technology increases. In order to cope with resource limitations of mobile-based environments, it is a common practice to delegate processing intensive components to a Cloud Computing infrastructure. In this scenario, executions of server-based jobs are still dependent on the local variations of the end-user context. We claim that there is a need for an advanced model for smarter services that combines techniques of context awareness and adaptive job scheduling. This model aims at rationalising the resource utilisation in a Cloud Computing environment, while leading to significant improvement of quality of service. In this paper, we introduce such a model and describe its performance benefits through a combination of social and service simulations. We analyse the results by demonstrating gains in performance, quality of service, reduction of wasted jobs, and improvement of overall end-user experience.

Collaboration and Social Computing in Emerging Financial Services

In this workshop we consider new financial services from a CSCW and Social Computing perspective. We will bring together researchers, policy-makers and practitioners who are interested in new financial services such as mobile payments, digital money, microfinance, mobile commerce, and the adoption and use of these new services by special sub-populations. Also of interest in this workshop will be the use of social analytics to understand financial markets and create new services. We also aim to explore the underlying group and network mechanisms that promote trust and enable commerce (e.g., solidarity lending groups). The workshop will contribute to the continued development of a network of researchers and practitioners interested in the intersection of HCI and financial services.

Leveraging attention scarcity to improve the overall user experience of Cloud services

Applications for mobile devices are increasingly relying on Cloud services to provide content and offload data processing tasks. Traditionally, web-based systems have been optimised to improve response time. Touch sensitive screens and the various sensors of mobile devices allow for better instrumentation, enabling providers to obtain more honest signals on how users utilise a service and learn about their behaviours. This work introduces an architecture that explores honest signals to determine a few user behaviours, e.g. the tendency to perform multiple tasks at a time, change focus, and expect fast response from a service. The architecture relies on a novel resource management strategy that considers such behaviours to prioritise service requests from users who demand fast response from a service. By comparing the proposed strategy with one that does not consider the signals, we show that the experience of users who demand faster response time can be improved without degrading the quality of service of those who often perform multiple activities. The proposed strategy also brings benefits to service providers as no additional resources are necessary to enhance overall user experience, which we modelled using Prospect Theory.

Understanding Fiado : Informal Credit in Brazil

This paper will explore insights gathered from fieldwork activities in the Northeast Brazil to design a financial application to facilitate access to credit. We observed the everyday financial practices of small merchants, their social physical networks and mechanisms to promote trust in those communities. We observed a particular kind of transaction that was common amongst our participants - called Fiado. Fiado transactions are a store credit practice in which merchants sell products to a customer based on trust that the customer will pay for it in the future. The Financial app aims to assist small merchants to manage their Fiado and their business.

Design Process of a Social Network System for Storage and Share Files in the Workplace

This paper explores the design process of a social network based storage and share application in the workplace. One of the big challenges of our era is to handle the amount of data available. This may result in a high cost with additional servers to store the data and guarantee availability and reliability. We interviewed ten employees to understand better their share and storage practices in everyday life, and also identify opportunities to inspire the design of storage applications. As a result, we provided 20 recommendations to develop social network storage systems. Additionally, we created personas and scenarios inspired by interviewed participants. We envisioned how the system should work and we illustrated it by interaction cycles with a low-tech prototype. Finally, we provide lessons learned towards the design of storage and share files in the workplace leveraging the social relationship amongst co-workers.