Catálogo de publicaciones - revistas

<jats:p>Research and industry increasingly make use of large amounts of data to guide decision-making. To do this, however, data needs to be analyzed in typically nontrivial refinement processes, which require technical expertise about methods and algorithms, experience with how a precise analysis should proceed, and knowledge about an exploding number of analytic approaches. To alleviate these problems, a plethora of different systems have been proposed that “intelligently” help users to analyze their data.</jats:p><jats:p>This article provides a first survey to almost 30 years of research on intelligent discovery assistants (IDAs). It explicates the types of help IDAs can provide to users and the kinds of (background) knowledge they leverage to provide this help. Furthermore, it provides an overview of the systems developed over the past years, identifies their most important features, and sketches an ideal future IDA as well as the challenges on the road ahead.</jats:p>

<jats:p>Moving from a set of independent virtual worlds to an integrated network of 3D virtual worlds or Metaverse rests on progress in four areas: immersive realism, ubiquity of access and identity, interoperability, and scalability. For each area, the current status and needed developments in order to achieve a functional Metaverse are described. Factors that support the formation of a viable Metaverse, such as institutional and popular interest and ongoing improvements in hardware performance, and factors that constrain the achievement of this goal, including limits in computational methods and unrealized collaboration among virtual world stakeholders and developers, are also considered.</jats:p>

<jats:p>As data-intensive, network-based applications proliferate, the power consumed by the data-center storage subsystem surges. This survey summarizes, organizes, and integrates a decade of research on power-aware enterprise storage systems. All of the existing power-reduction techniques are classified according to the disk-power factor and storage-stack layer addressed. A majority of power-reduction techniques is based on dynamic power management. We also consider alternative methods that reduce disk access time, conserve space, or exploit energy-efficient storage hardware. For every energy-conservation technique, the fundamental trade-offs between power, capacity, performance, and dependability are uncovered. With this survey, we intend to stimulate integration of different power-reduction techniques in new energy-efficient file and storage systems.</jats:p>

<jats:p>This survey provides a structured and comprehensive overview of research on security and privacy in computer and communication networks that use game-theoretic approaches. We present a selected set of works to highlight the application of game theory in addressing different forms of security and privacy problems in computer networks and mobile applications. We organize the presented works in six main categories: security of the physical and MAC layers, security of self-organizing networks, intrusion detection systems, anonymity and privacy, economics of network security, and cryptography. In each category, we identify security problems, players, and game models. We summarize the main results of selected works, such as equilibrium analysis and security mechanism designs. In addition, we provide a discussion on the advantages, drawbacks, and future direction of using game theory in this field. In this survey, our goal is to instill in the reader an enhanced understanding of different research approaches in applying game-theoretic methods to network security. This survey can also help researchers from various fields develop game-theoretic solutions to current and emerging security problems in computer networking.</jats:p>

<jats:p>The emergence of new Internet paradigms has changed the common properties of network data, increasing the bandwidth consumption and balancing traffic in both directions. These facts raise important challenges, making it necessary to devise effective solutions for managing network traffic. Since traditional methods are rather ineffective and easily bypassed, particular attention has been paid to the development of new approaches for traffic classification. This article surveys the studies on peer-to-peer traffic detection and classification, making an extended review of the literature. Furthermore, it provides a comprehensive analysis of the concepts and strategies for network monitoring.</jats:p>

<jats:p> This article reviews four popular mathematical formalisms— <jats:italic>queueing theory, network calculus, schedulability analysis</jats:italic> , and <jats:italic>dataflow analysis</jats:italic> —and how they have been applied to the analysis of on-chip communication performance in Systems-on-Chip. The article discusses the basic concepts and results of each formalism and provides examples of how they have been used in Networks-on-Chip (NoCs) performance analysis. Also, the respective strengths and weaknesses of each technique and its suitability for a specific purpose are investigated. An open research issue is a unified analytical model for a comprehensive performance evaluation of NoCs. To this end, this article reviews the attempts that have been made to bridge these formalisms. </jats:p>

<jats:p>Low power and/or energy consumption is a requirement not only in embedded systems that run on batteries or have limited cooling capabilities, but also in desktop and mainframes where chips require costly cooling techniques. Since the cache subsystem is typically the most power/energy-consuming subsystem, caches are good candidates for power/energy optimizations, and therefore, cache tuning techniques are widely researched. This survey focuses on state-of-the-art offline static and online dynamic cache tuning techniques and summarizes the techniques' attributes, major challenges, and potential research trends to inspire novel ideas and future research avenues.</jats:p>

<jats:p>The ever-growing computation and storage capability of mobile phones have given rise to mobile-centric context recognition systems, which are able to sense and analyze the context of the carrier so as to provide an appropriate level of service. As nonintrusive autonomous sensing and context recognition are desirable characteristics of a personal sensing system; efforts have been made to develop opportunistic sensing techniques on mobile phones. The resulting combination of these approaches has ushered in a new realm of applications, namely<jats:italic>opportunistic user context recognition with mobile phones</jats:italic>.</jats:p><jats:p>This article surveys the existing research and approaches towards realization of such systems. In doing so, the typical architecture of a mobile-centric user context recognition system as a sequential process of<jats:italic>sensing</jats:italic>,<jats:italic>preprocessing</jats:italic>, and<jats:italic>context recognition</jats:italic>phases is introduced. The main techniques used for the realization of the respective processes during these phases are described, and their strengths and limitations are highlighted. In addition, lessons learned from previous approaches are presented as motivation for future research. Finally, several open challenges are discussed as possible ways to extend the capabilities of current systems and improve their real-world experience.</jats:p>

<jats:p>The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to the existence of an already large amount of near-duplicate content. This imposes urgent demands on near-duplicate video retrieval as a key role in novel tasks such as video search, video copyright protection, video recommendation, and many more. Driven by its significance, near-duplicate video retrieval has recently attracted a lot of attention. As discovered in recent works, latest improvements and progress in near-duplicate video retrieval, as well as related topics including low-level feature extraction, signature generation, and high-dimensional indexing, are employed to assist the process.</jats:p> <jats:p>As we survey the works in near-duplicate video retrieval, we comparatively investigate existing variants of the definition of near-duplicate video, describe a generic framework, summarize state-of-the-art practices, and explore the emerging trends in this research topic.</jats:p>

<jats:p>The need for flexible customization of large feature-rich software systems, according to requirements of various stakeholders, has become an important problem in software development. Among the many software engineering approaches dealing with variability management, the notion of Software Product Line (SPL) has emerged as a major unifying concept. Drawing from established disciplines of manufacturing, SPL approaches aim to design repertoires of software artifacts, from which customized software systems for specific stakeholder requirements can be developed. A major difficulty SPL approaches attempt to address is the modularization of software artifacts, which reconciles the user's needs for certain features and the development and technical constraints. Towards this end, many SPL approaches use feature diagrams to describe possible configurations of a feature set. There have been several proposals for feature diagram languages with varying degrees of expressiveness, intuitiveness, and precision. However, these feature diagram languages have limited scalability when applied to realistic software systems. This article provides a systematic survey of various concerns of feature diagrams and ways in which concerns have been separated. The survey shows how the uncertainty in the purpose of feature diagram languages creates both conceptual and practical limitations to scalability of those languages.</jats:p>