Abstract-Cloud computing has evolved from the provisioning of virtual machines to the provisioning of complex services, delivered to customers under the terms of Service-Level Agreements (SLAs). SLAs specify the Quality of Service (QoS) that should be provided to customers as well as the billing model. A main concern for cloud service providers is to maintain the agreed SLA terms in order to avoid losses and penalties. Maintaining the SLA in turn requires translating the QoS to configurations of low-level mechanisms, able to enforce the agreed terms. Current systems provide no integrated support for SLA specification, translation, and enforcement. In this paper, we propose an approach for specifying and enforcing SLAs for cloud service providers. The approach covers the creation of SLA templates under a billing model, the design of performance and faulttolerance QoS assurance mechanisms as well as the translation of QoS to appropriate configurations of those mechanisms. We demonstrate the feasibility of our approach by using the Qu4DS framework for PaaS cloud providers. Moreover, we evaluate the impact of failures on the provider profit. The experiments were carried out on the Grid5000 testbed and demonstrate the effectiveness of ensuring fault tolerance in different scenarios.

Predicting case outcomes is useful for legal professionals to understand case law, file a lawsuit, raise a defense, or lodge appeals, for instance. However, it is very hard to predict legal decisions since this requires extracting valuable information from myriads of cases and other documents. Moreover, legal system complexity along with a huge volume of litigation make this problem even harder. This paper introduces an approach to predicting Brazilian court decisions, including whether they will be unanimous. Our methodology uses various machine learning algorithms, including classifiers and state-of-the-art Deep Learning models. We developed a working prototype whose F1-score performance is ~80.2% by using 4,043 cases from a Brazilian court. To our knowledge, this is the first study to present methods for predicting Brazilian court decision outcomes.

Abstract-A main challenge for service providers is managing service-level agreements (SLAs) with their customers while satisfying their business objectives, such as maximizing profits. Most current systems fail to consider business objectives and thus to provide a complete SLA management solution. This work proposes an SLA-driven management solution that aims to maximize the provider's profit by reducing resource costs as well as fines owning to SLA violations. Specifically, this work proposes a framework that comprises multiple, configurable control loops and supports automatically adjusting service configurations and resource usage in order to maintain SLAs in the most costeffective way. The framework targets services implemented on top of large-scale distributed infrastructures, such as clouds. Experimental results demonstrate its effectiveness in maintaining SLAs while reducing provider costs.