Computer Science Department

Capacity management of a hosting infrastructure has traditionally focused only on performance goals. However, the quality of service provided to the hosted applications, and ultimately the revenues achieved by the provider, depend also on other aspects, such as security and energy constraints. This paper extends our self-adaptive SLA-driven capacity management solution to capture, in an unified framework, key performance and cost tradeoffs that arise when operating under security attacks and energy constraints. A number of scenarios and strategies based on dynamic SLA contracts are designed to help uncover, via simulation experiments, the main tradeoffs, considering both the provider's interests (i.e., revenues) and the customer's interests (i.e., legitimate throughput, response time distribution and costs). Finally, we also assess the cost-effectiveness of our framework under highly variable application service times.

Capacity management of a hosting infrastructure has traditionally focused only on performance goals. However, the quality of service provided to the hosted applications and the revenues achieved by the provider, depend also on other aspects, such as security and energy constraints. This paper extends our self-adaptive SLA-driven capacity management solution to capture key performance and cost tradeoffs that arise when operating under security attacks and energy constraints. A number of scenarios and strategies based on dynamic SLA contracts are designed to help uncover the main tradeoffs considering both the provider's interests and the customers's interests.

In this work we present an extension of our previous capacity management framework making it robust to security attacks. In a scenario where multiple applications are hosted in a shared infrastructure, our performance and optimization models are extended to minimize the impact of security attacks on the provider's revenue and applications' QoS. A number of scenarios and strategies based on dynamic SLA contracts are designed to help uncover the main tradeoffs considering both the provider's interests and the customer's interests.

Performance modeling is a central task in the capacity management of server platforms. Traditional performance models are created for transactional workloads (purely open models), batch or interactive (purely closed models). However, many real Web applications experience session-based workloads that exhibit a partially-open behavior, which includes components from either open or closed model, particularly with respect to response time. In this paper, we developed an analytical model for performance that captures the main aspects of partially-open workloads of multi-layered Web platforms and compared it with the open and closed models by simulation. Resumo. A modelagem de desempenhoé uma tarefa central para o gerenciamento de capacidade de plataformas servidoras. Modelos de desempenho tradicionais são derivados para cargas de trabalho transacionais (modelos puramente abertos), batch ou interativas (modelos puramente fechados). Entretanto, várias aplicações reais da Web consistem em cargas baseadas em sessões com comportamento semi-aberto que incluem componentes dos modelos abertos e fechados, particularmente em relação ao tempo de resposta. Neste artigo, desenvolvemos um modelo analítico de desempenho que captura aspectos de cargas semi-abertas para plataformas Web multi-camadas e analisamos seus compromissos em relação aos modelos fechado e aberto por meio de simulação.

Recommender systems are quickly becoming ubiquitous in applications such as e-commerce, social media channels, and content providers, among others, acting as an enabling mechanism designed to overcome the information overload problem by improving browsing and consumption experience. A typical task in many recommender systems is to output a ranked list of items, so that items placed higher in the rank are more likely to be interesting to the users. Interestingness measures include how accurate, novel, and diverse are the suggested items, and the objective is usually to produce ranked lists optimizing one of these measures. Suggesting items that are simultaneously accurate, novel, and diverse is much more challenging, since this may lead to a conflicting-objective problem, in which the attempt to improve a measure further may result in worsening other measures. In this article, we propose new approaches for multiobjective recommender systems based on the concept of Pareto efficiency—a...

Os indicadores de quantidade de doença numa po¬ pulação: prevalência e incidência, a nível de efectivo ea nível animal, permitem avaliar o progresso realiza¬ do no controlo de doenças. Os valores calculados para estes indicadores são relevantes para os decisores de saúde animal optarem por manter ou por adaptar/modi¬ ficar a combinação de métodos de controlo/vigilância integrados num determinado programa. Consequente¬ mente, é desejável que as estimativas da prevalência e da incidência reflictam a realidade.

Abstract In recent years, social media users are voluntarily making large volume of personal data available on the social networks. Such data (eg, professional associations) can create opportunities for users to strengthen their social and professional ties. However, the same data can also be used against the user for viral marketing and other unsolicited purposes. The invasion of privacy occurs due to privacy unawareness and carelessness of making information publicly available.

Understanding how users navigate and interact when they connect to social networking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, we present an in-depth analysis of user workloads in online social networks. This study is based on detailed clickstream data, collected over a 12-day period, summarizing HTTP sessions of 37,024 users who accessed four popular social networks: Orkut, MySpace, Hi5, and LinkedIn.

Abstract—With the growing popularity and usage of online social media services, people now have accounts (some times several) on multiple and diverse services like Facebook, LinkedIn, Twitter and YouTube. Publicly available information can be used to create a digital footprint of any user using these social media services. Generating such digital footprints can be very useful for personalization, profile management, detecting malicious behavior of users.

Resumo. Máquinas Virtuais (VMs) oferecem um ambiente adequado para consolidar múltiplos serviços em poucas máquinas, reduzindo custos de aquisiç ao e gerenciamento. As principais questoes antes da migraç ao de uma infraestrutura de TI para um ambiente virtual estao ligadas ao desempenho das aplicaçoes e serviços no novo ambiente. Este artigo propoe um arcabouço para prever o desempenho de aplicaçoes em ambientes virtuais.

Abstract E-commerce services have become a promising and profitable application of the Internet. In order to keep them growing, solutions must be found to deal with unreliable connections and high latencies, among other problems. The best solutions to such problems tend to depend on the distribution of the service over the network, placing servers in multiple locations, closer to customers. If placement of servers is effective it tends to reduce delays and traffic-related costs.

Resumo. Entender as características da carga de trabalho é uma tarefa fundamental para o provedor de acesso à Internet de banda larga melhorar o gerenciamento da sua infra-estrutura. Este artigo apresenta uma metodologia para caracterização do comportamento do usuário da Internet de banda larga, bem como analisa e discute os resultados de sua aplicação com dados reais de tráfego recente. A caracterização de 1, 88 milhão de sessões foi realizada em três níveis hierárquicos.

Server performance has become a crucial issue for improving the overall performance of the World-Wide Web. This paper describes Webmonitor, a tool for evaluating and understanding server performance, and presents new results for a realistic workload. Webmonitor measures activity and resource consumption, both within the kernel and in HTTP processes running in user space. Webmonitor is implemented using an efficient combination of sampling and event-driven techniques that exhibit low overhead.

Using Internet to predict elections has been a topic of interest for different fields. Researchers from Google have showed an approach employing user's queries on that search engine [4]. Other site, The Daily Beast, has create an “Election Oracle”[1], scanning 40,000 blogs and social media sites and applying a sentiment analysis to made their predictions. In both these case, the predictions are expressed as a likelihood of winning and not the total amount candidate votes or percent expected.

Abstract In information networks where users send messages to one another, the issue of information overload naturally arises: which are the most important messages? In this paper we study the problem of understanding the importance of messages in Twitter. We approach this problem in two stages. First, we perform an extensive characterization of a very large Twitter dataset which includes all users, social relations, and messages posted from the beginning of the service up to August 2009.

ABSTRACT The Web is home for a plethora of virtual communities, ranging from friendship networks (eg, MySpace) to those targeted to commercial transactions (eg, Amazon. com) or content sharing (eg, YouTube). Collecting and analyzing such networks is a task pursued by many researchers lately. However, previous works usually relied on ad-hoc techniques for gathering sample network topologies. In this work we present a system able to collect virtually any Webbased network and make it readily available for analysis.

ABSTRACT Online Social Networks (OSNs) such as Facebook and Twitter have experienced exponential growth in recent years. Users are spending more time on OSNs than on any other sites and services on the Internet. Users post and share a lot of personal information on these sites without being aware of privacy implications or simply not caring much about them, what turns to be a treasure for marketing companies and cyber criminals.

Resumo. O grande volume de tráfego de e-mails indesejados (spam) que circulam na Internet consome recursos que poderiam ser melhor utilizados. Entender as características do tráfego SMTP (Simple Mail Transfer Protocol), sob o ponto de vista do provedor de acesso, é tarefa fundamental para propor mecanismos que permitam o bloqueio de mensagens indesejadas na origem.

Resumo. O crescimento do tráfego na Internet derivado dos vıdeos gerados por usuários motivou este trabalho. Busca-se entender caracterısticas dos usuários e dos vıdeos de quatro sistemas de compartilhamento de vıdeos. O foco é voltado para a origem do tráfego e para a evoluçao temporal de vıdeos tanto recentemente adicionados quanto já populares.