Catálogo de publicaciones - revistas

<jats:p>Cyber-security systems, which protect networks and computers against cyber attacks, are becoming common due to increasing threats and government regulation. At the same time, the enormous amount of data gathered by cyber-security systems poses a serious threat to the privacy of the people protected by those systems. To ground this threat, we survey common and novel cyber-security technologies and analyze them according to the potential for privacy invasion. We suggest a taxonomy for privacy risks assessment of information security technologies, based on the level of data exposure, the level of identification of individual users, the data sensitivity and the user control over the monitoring, and collection and analysis of the data. We discuss our results in light of the recent technological trends and suggest several new directions for making these mechanisms more privacy-aware.</jats:p>

<jats:p>Software deficiencies are minimized by utilizing recommended software development and quality assurance practices. However, these recommended practices (i.e., quality practices) become ineffective if software professionals purposefully ignore them. Conducting a systematic literature review (n = 4,838), we discovered that only a small number of previous studies, within software engineering and information systems literature, have investigated the omission of quality practices. These studies explain the omission of quality practices mainly as a result of organizational decisions and trade-offs made under resource constraints or market pressure. However, our study indicates that different aspects of this phenomenon deserve further research. In particular, future research must investigate the conditions triggering the omission of quality practices and the processes through which this phenomenon occurs. Especially, since software development is a human-centric phenomenon, the psychological and behavioral aspects of this process deserve in-depth empirical investigation. In addition, futures research must clarify the social, organizational, and economical consequences of ignoring quality practices. Gaining in-depth theoretically sound and empirically grounded understandings about different aspects of this phenomenon enables research and practice to suggest interventions to overcome this issue.</jats:p>

<jats:p>Pilot-Job systems play an important role in supporting distributed scientific computing. They are used to execute millions of jobs on several cyberinfrastructures worldwide, consuming billions of CPU hours a year. With the increasing importance of task-level parallelism in high-performance computing, Pilot-Job systems are also witnessing an adoption beyond traditional domains. Notwithstanding the growing impact on scientific research, there is no agreement on a definition of Pilot-Job system and no clear understanding of the underlying abstraction and paradigm. Pilot-Job implementations have proliferated with no shared best practices or open interfaces and little interoperability. Ultimately, this is hindering the realization of the full impact of Pilot-Jobs by limiting their robustness, portability, and maintainability. This article offers a comprehensive analysis of Pilot-Job systems critically assessing their motivations, evolution, properties, and implementation. The three main contributions of this article are as follows: (1) an analysis of the motivations and evolution of Pilot-Job systems; (2) an outline of the Pilot abstraction, its distinguishing logical components and functionalities, its terminology, and its architecture pattern; and (3) the description of core and auxiliary properties of Pilot-Jobs systems and the analysis of six exemplar Pilot-Job implementations. Together, these contributions illustrate the Pilot paradigm, its generality, and how it helps to address some challenges in distributed scientific computing.</jats:p>

<jats:p>As applications and operating systems are becoming more complex, the last decade has seen the rise of many tracing tools all across the software stack. This article presents a hands-on comparison of modern tracers on Linux systems, both in user space and kernel space. The authors implement microbenchmarks that not only quantify the overhead of different tracers, but also sample fine-grained metrics that unveil insights into the tracers’ internals and show the cause of each tracer’s overhead. Internal design choices and implementation particularities are discussed, which helps us to understand the challenges of developing tracers. Furthermore, this analysis aims to help users choose and configure their tracers based on their specific requirements to reduce their overhead and get the most of out of them.</jats:p>

<jats:p>This article is a tutorial for researchers who are designing software to perform a creative task and want to evaluate their system using interdisciplinary theories of creativity. Researchers who study human creativity have a great deal to offer computational creativity. We summarize perspectives from psychology, philosophy, cognitive science, and computer science as to how creativity can be measured both in humans and in computers. We survey how these perspectives have been used in computational creativity research and make recommendations for how they should be used.</jats:p>

<jats:p>In the context of the emergent Software-Defined Networking (SDN) paradigm, the attention is mostly directed to the evolution of control protocols and networking functionalities. However, network professionals also need the right tools to reach the same level—and beyond—of monitoring and control they have in traditional networks. Current SDN tools are developed on an ad hoc basis, for specific SDN frameworks, while production environments demand standard platforms and easy integration. This survey aims to foster the definition of the next generation SDN management framework by providing the readers a thorough overview of existing SDN tools and main research directions.</jats:p>

<jats:p>We present a comprehensive survey on parallel I/O in the high-performance computing (HPC) context. This is an important field for HPC because of the historic gap between processing power and storage latency, which causes application performance to be impaired when accessing or generating large amounts of data. As the available processing power and amount of data increase, I/O remains a central issue for the scientific community. In this survey article, we focus on a traditional I/O stack, with a POSIX parallel file system. We present background concepts everyone could benefit from. Moreover, through the comprehensive study of publications from the most important conferences and journals in a 5-year time window, we discuss the state of the art in I/O optimization approaches, access pattern extraction techniques, and performance modeling, in addition to general aspects of parallel I/O research. With this approach, we aim at identifying the general characteristics of the field and the main current and future research topics.</jats:p>

<jats:p>Despite the increasing use of social media platforms for information and news gathering, its unmoderated nature often leads to the emergence and spread of rumours, i.e., items of information that are unverified at the time of posting. At the same time, the openness of social media platforms provides opportunities to study how users share and discuss rumours, and to explore how to automatically assess their veracity, using natural language processing and data mining techniques. In this article, we introduce and discuss two types of rumours that circulate on social media: long-standing rumours that circulate for long periods of time, and newly emerging rumours spawned during fast-paced events such as breaking news, where reports are released piecemeal and often with an unverified status in their early stages. We provide an overview of research into social media rumours with the ultimate goal of developing a rumour classification system that consists of four components: rumour detection, rumour tracking, rumour stance classification, and rumour veracity classification. We delve into the approaches presented in the scientific literature for the development of each of these four components. We summarise the efforts and achievements so far toward the development of rumour classification systems and conclude with suggestions for avenues for future research in social media mining for the detection and resolution of rumours.</jats:p>

<jats:p>Event processing (EP) is a data processing technology that conducts online processing of event information. In this survey, we summarize the latest cutting-edge work done on EP from both industrial and academic research community viewpoints. We divide the entire field of EP into three subareas: EP system architectures, EP use cases, and EP open research topics. Then we deep dive into the details of each subsection. We investigate the system architecture characteristics of novel EP platforms, such as Apache Storm, Apache Spark, and Apache Flink. We found significant advancements made on novel application areas, such as the Internet of Things; streaming machine learning (ML); and processing of complex data types such as text, video data streams, and graphs. Furthermore, there has been significant body of contributions made on event ordering, system scalability, development of EP languages and exploration of use of heterogeneous devices for EP, which we investigate in the latter half of this article. Through our study, we found key areas that require significant attention from the EP community, such as Streaming ML, EP system benchmarking, and graph stream processing.</jats:p>

<jats:p>In the last few decades, Structure from Motion (SfM) and visual Simultaneous Localization and Mapping (visual SLAM) techniques have gained significant interest from both the computer vision and robotic communities. Many variants of these techniques have started to make an impact in a wide range of applications, including robot navigation and augmented reality. However, despite some remarkable results in these areas, most SfM and visual SLAM techniques operate based on the assumption that the observed environment is static. However, when faced with moving objects, overall system accuracy can be jeopardized. In this article, we present for the first time a survey of visual SLAM and SfM techniques that are targeted toward operation in dynamic environments. We identify three main problems: how to perform reconstruction (robust visual SLAM), how to segment and track dynamic objects, and how to achieve joint motion segmentation and reconstruction. Based on this categorization, we provide a comprehensive taxonomy of existing approaches. Finally, the advantages and disadvantages of each solution class are critically discussed from the perspective of practicality and robustness.</jats:p>