Abstract
On-line applications and services are now a critical part of our everyday life. Using these services typically requires us to trust our personal or company's information to a large number of third-party entities. These entities enforce several security measures to avoid unauthorized accesses but data is still stored on common database systems that are designed without data privacy concerns in mind. As a result, data is vulnerable against anyone with direct access to the database, which may be external attackers, malicious insiders, spies or even subpoenas. Building strong data privacy mechanisms on top of common database systems is possible but has a significant impact on the system's resources, computational capabilities and performance. Notably, the amount of useful computation that may be done over strongly encrypted data is close to none, which defeats the purpose of offloading computation to third-party services. In this paper, we propose to shift the need to trust in the honesty and security of service providers to simply trust that they will not collude. This is reasonable as cloud providers, being competitors, do not share data among themselves. We focus on NoSQL databases and present SafeRegions, a novel prototype of a distributed and secure NoSQL database that is built on top of HBase and that guarantees strong data privacy while still providing most of HBase's query capabilities. SafeRegions relies on secret sharing and multiparty computation techniques to provide a NoSQL database built on top of multiple, non-colluding service providers that appear as a single one to the user. Strikingly, service providers, individually, cannot disclose any of the user's data but, together, are able to offer data storage and processing capabilities. Additionally, we evaluate SafeRegions exposing performance trade-offs imposed by security mechanisms and provide useful insights for future research on performance optimization.

Abstract
In the pursuit of highly available systems, storage systems began offering eventually consistent data models. These models are suitable for a number of applications but not applicable for all. In this paper we discuss a system that can offer a eventually consistent data model but can also, when needed, offer a strong consistent one.

Abstract
The development of ETL systems has been the target of many research efforts to support its development and implementation. In the last few years, we presented a pattern-oriented approach to develop these systems. Basically, patterns are comprised by a set of abstract components that can be configured to enable its instantiation for specific scenarios. Even when using high-level components, the ETL systems are very specific processes that represent complex data requirements and transformation routines. Several operational requirements need to be configured and system correctness is hard to validate, which can result in several implementation problems. In this paper, a set of formal specifications in Alloy is presented to express the structural constraints and behaviour of a slowly changing dimension pattern. Then, specific physical models can be generated based on formal specifications and constraints defined in an Alloy model, helping to ensure the correctness of the configuration provided.

Abstract
In the last few years, sustainability has become one of the priority lines for many companies and organizations, especially public administrations. This trend has been even more evident in some regions where the preservation of natural resources is of utmost importance, not only from an environmental perspective, but also from an economic one. In this context, technology has become one of the key factors to achieve sustainability goals. An example of these technologies are Unmanned Aerial Vehicles (UAVs) which are being used more and more with sustainability purposes. However, although some efforts have been made to propose software approaches to model sustainability, some examples that model the impact of technology on sustainability are still needed. This paper presents an instance of a sustainability metamodel for the UAVs domain. This model allows to specify the impact of UAV-based processes on sustainability, and also to identify potential limitations that may hinder its applicability. Finally, the paper provides some suggestions to complete the metamodel based on the instantiation process.

Abstract

Abstract
Nowadays, many companies have migrated their applications and data to the cloud. Among other benefits of this technology, the ability to answer quickly business requirements has been one of the main motivations. Thereby, in cloud environments, resources should be acquired and released automatically and quickly at runtime. This way, to ensure QoS, the major cloud providers emphasize ensuring of availability, CPU instance and cost measure in their SLAs (Service Level Agreements). However, the QoS performance are not completely handled or inappropriately treated in SLAs. Although from the user's point of view, it is considered one of the main QoS parameters. Therefore, the aim of this work consists in development of a solution to efficient query processing on large databases available in the cloud environments. It integrates adaptive re-optimization at query runtime and their costs are based on the SRT (Service Response Time) QoS performance parameter of SLA. Finally, the solution was evaluated in Amazon EC2 cloud infrastructure and the TPC-DS like benchmark was used for generating a database.