Catálogo de publicaciones - revistas

<jats:p>Thread-Level Speculation (TLS) is a promising technique that allows the parallel execution of sequential code without relying on a prior, compile-time-dependence analysis. In this work, we introduce the technique, present a taxonomy of TLS solutions, and summarize and put into perspective the most relevant advances in this field.</jats:p>

<jats:p>Sentiment analysis in Twitter is a field that has recently attracted research interest. Twitter is one of the most popular microblog platforms on which users can publish their thoughts and opinions. Sentiment analysis in Twitter tackles the problem of analyzing the tweets in terms of the opinion they express. This survey provides an overview of the topic by investigating and briefly describing the algorithms that have been proposed for sentiment analysis in Twitter. The presented studies are categorized according to the approach they follow. In addition, we discuss fields related to sentiment analysis in Twitter including Twitter opinion retrieval, tracking sentiments over time, irony detection, emotion detection, and tweet sentiment quantification, tasks that have recently attracted increasing attention. Resources that have been used in the Twitter sentiment analysis literature are also briefly presented. The main contributions of this survey include the presentation of the proposed approaches for sentiment analysis in Twitter, their categorization according to the technique they use, and the discussion of recent research trends of the topic and its related fields.</jats:p>

<jats:p>Collaborative filtering is among the most preferred techniques when implementing recommender systems. Recently, great interest has turned toward parallel and distributed implementations of collaborative filtering algorithms. This work is a survey of parallel and distributed collaborative filtering implementations, aiming to not only provide a comprehensive presentation of the field's development but also offer future research directions by highlighting the issues that need to be developed further.</jats:p>

<jats:p>The last decade witnessed a tremendous increase in popularity and usage of social network services, such as Facebook, Twitter, and YouTube. Moreover, advances in Web technologies coupled with social networks has enabled users to not only access, but also generate, content in many forms. The overwhelming amount of produced content and resulting network traffic gives rise to precarious scalability issues for social networks, such as handling a large number of users, infrastructure management, internal network traffic, content dissemination, and data storage. There are few surveys conducted to explore the different dimensions of social networks, such as security, privacy, and data acquisition. Most of the surveys focus on privacy or security-related issues and do not specifically address scalability challenges faced by social networks. In this survey, we provide a comprehensive study of social networks along with their significant characteristics and categorize social network architectures into three broad categories: (a) centralized, (b) decentralized, and (c) hybrid. We also highlight various scalability issues faced by social network architectures. Finally, a qualitative comparison of presented architectures is provided, which is based on various scalability metrics, such as availability, latency, interserver communication, cost of resources, and energy consumption, just to name a few.</jats:p>

<jats:p>Publish/subscribe (pub/sub) is an attractive communication paradigm for large-scale distributed applications running across multiple administrative domains. Pub/sub allows event-based information dissemination based on constraints on the nature of the data rather than on pre-established communication channels. It is a natural fit for deployment in untrusted environments such as public clouds linking applications across multiple sites. However, pub/sub in untrusted environments leads to major confidentiality concerns stemming from the content-centric nature of the communications. This survey classifies and analyzes different approaches to confidentiality preservation for pub/sub, from applications of trust and access control models to novel encryption techniques. It provides an overview of the current challenges posed by confidentiality concerns and points to future research directions in this promising field.</jats:p>

<jats:p>Numerous behavioral or physiological biometric traits, including iris, signature, hand geometry, speech, palm print, face, etc. have been used to discriminate individuals in a number of security applications over the last 30 years. Among these, hand-based biometric systems have come to the attention of researchers worldwide who utilize them for low- to medium-security applications such as financial transactions, access control, law enforcement, border control, computer security, time and attendance systems, dormitory meal plan access, etc. Several approaches for biometric recognition have been summarized in the literature. The survey in this article focuses on the interface between various hand modalities, summary of inner- and dorsal-knuckle print recognition, and fusion techniques. First, an overview of various feature extraction and classification approaches for knuckle print, a new entrant in the hand biometrics family with a higher user acceptance and invariance to emotions, is presented. Next, knuckle print fusion schemes with possible integration scenarios, and traditional capturing devices have been discussed. The economic relevance of various biometric traits, including knuckle print for commercial and forensic applications is debated. Finally, conclusions related to the scope of knuckle print as a biometric trait are drawn and some recommendations for the development of hand-based multimodal biometrics have been presented.</jats:p>

<jats:p>Heap data is potentially unbounded and seemingly arbitrary. Hence, unlike stack and static data, heap data cannot be abstracted in terms of a fixed set of program variables. This makes it an interesting topic of study and there is an abundance of literature employing heap abstractions. Although most studies have addressed similar concerns, insights gained in one description of heap abstraction may not directly carry over to some other description.</jats:p> <jats:p> In our search of a unified theme, we view <jats:italic>heap abstraction</jats:italic> as consisting of two steps: (a) <jats:italic>heap modelling</jats:italic> , which is the process of representing a heap memory (i.e., an unbounded set of concrete locations) as a heap model (i.e., an unbounded set of abstract locations), and (b) <jats:italic>summarization</jats:italic> , which is the process of bounding the heap model by merging multiple abstract locations into summary locations. We classify the heap models as storeless, store based, and hybrid. We describe various summarization techniques based on <jats:italic>k</jats:italic> -limiting, allocation sites, patterns, variables, other generic instrumentation predicates, and higher-order logics. This approach allows us to compare the insights of a large number of seemingly dissimilar heap abstractions and also paves the way for creating new abstractions by mix and match of models and summarization techniques. </jats:p>

<jats:p>The openness and extensibility of Android have made it a popular platform for mobile devices and a strong candidate to drive the Internet-of-Things. Unfortunately, these properties also leave Android vulnerable, attracting attacks for profit or fun. To mitigate these threats, numerous issue-specific solutions have been proposed. With the increasing number and complexity of security problems and solutions, we believe this is the right moment to step back and systematically re-evaluate the Android security architecture and security practices in the ecosystem. We organize the most recent security research on the Android platform into two categories: the software stack and the ecosystem. For each category, we provide a comprehensive narrative of the problem space, highlight the limitations of the proposed solutions, and identify open problems for future research. Based on our collection of knowledge, we envision a blueprint for engineering a secure, next-generation Android ecosystem.</jats:p>

<jats:p>Many real-world data-mining applications involve obtaining predictive models using datasets with strongly imbalanced distributions of the target variable. Frequently, the least-common values of this target variable are associated with events that are highly relevant for end users (e.g., fraud detection, unusual returns on stock markets, anticipation of catastrophes, etc.). Moreover, the events may have different costs and benefits, which, when associated with the rarity of some of them on the available training data, creates serious problems to predictive modeling techniques. This article presents a survey of existing techniques for handling these important applications of predictive analytics. Although most of the existing work addresses classification tasks (nominal target variables), we also describe methods designed to handle similar problems within regression tasks (numeric target variables). In this survey, we discuss the main challenges raised by imbalanced domains, propose a definition of the problem, describe the main approaches to these tasks, propose a taxonomy of the methods, summarize the conclusions of existing comparative studies as well as some theoretical analyses of some methods, and refer to some related problems within predictive modeling.</jats:p>

<jats:p>This article provides background information about interconnection networks, an analysis of previous developments, and an overview of the state of the art. The main contribution of this article is to highlight the importance of the interpolation and extrapolation of technological changes and physical constraints in order to predict the optimum future interconnection network. The technological changes are related to three of the most important attributes of interconnection networks: topology, routing, and flow-control algorithms. On the other hand, the physical constraints, that is, port counts, number of communication nodes, and communication speed, determine the realistic properties of the network. We present the state-of-the-art technology for the most commonly used interconnection networks and some background related to often-used network topologies. The interconnection networks of the best-performing petascale parallel computers from past and present Top500 lists are analyzed. The lessons learned from this analysis indicate that computer networks need better performance in future exascale computers. Such an approach leads to the conclusion that a high-radix topology with optical connections for longer links is set to become the optimum interconnect for a number of relevant application domains.</jats:p>