Catálogo de publicaciones - revistas

<jats:p>A large class of applications need to execute the same workflow on different datasets of identical size. Efficient execution of such applications necessitates intelligent distribution of the application components and tasks on a parallel machine, and the execution can be orchestrated by utilizing task, data, pipelined, and/or replicated parallelism. The scheduling problem that encompasses all of these techniques is called<jats:italic>pipelined workflow scheduling</jats:italic>, and it has been widely studied in the last decade. Multiple models and algorithms have flourished to tackle various programming paradigms, constraints, machine behaviors, or optimization goals. This article surveys the field by summing up and structuring known results and approaches.</jats:p>

<jats:p>Organizations perceive ERP as a vital tool for organizational competition as it integrates dispersed organizational systems and enables flawless transactions and production. This review examines studies investigating Critical Success Factors (CSFs) in implementing Enterprise Resource Planning (ERP) systems. Keywords relating to the theme of this study were defined and used to search known Web engines and journal databases for studies on both implementing ERP systems per se and integrating ERP systems with other well- known systems (e.g., SCM, CRM) whose importance to business organizations and academia is acknowledged to work in a complementary fashion. A total of 341 articles were reviewed to address three main goals. This study structures previous research by presenting a comprehensive taxonomy of CSFs in the area of ERP. Second, it maps studies, identified through an exhaustive and comprehensive literature review, to different dimensions and facets of ERP system implementation. Third, it presents studies investigating CSFs in terms of a specific ERP lifecycle phase and across the entire ERP life cycle. This study not only reviews articles in which an ERP system is the sole or primary field of research, but also articles that refer to an integration of ERP systems and other popular systems (e.g., SCM, CRM). Finally it provides a comprehensive bibliography of the articles published during this period that can serve as a guide for future research.</jats:p>

<jats:p>Resource discovery is an important part of distributed computing and resource sharing systems, like grids and utility computing. Because of the increasing importance of decentralized and peer-to-peer environments, characterized by high dynamism and churn, a number of resource discovery mechanisms, mainly based on peer-to-peer techniques, have been presented recently. We present and classify them according to criteria like their topology and the degree of achievement of various common requirements of great importance for the targeted environments, as well as compare their reported performance. These classifications intend to provide an intuitive vision of the strengths and weaknesses of each system.</jats:p>

<jats:p>Network virtualization provides a novel approach to running multiple concurrent virtual networks over a common physical network infrastructure. From a research perspective, this enables the networking community to concurrently experiment with new Internet architectures and protocols. From a market perspective, on the other hand, this paradigm is appealing as it enables infrastructure service providers to experiment with new business models that range from leasing virtual slices of their infrastructure to hosting multiple concurrent network services.</jats:p> <jats:p>In this article, we present the slice embedding problem and recent developments in the area. A slice is a set of virtual instances spanning a set of physical resources. The embedding problem consists of three main tasks: (1) resource discovery, which involves monitoring the state of the physical resources, (2) virtual network mapping, which involves matching users' requests with the available resources, and (3) allocation, which involves assigning the resources that match the users' requests.</jats:p> <jats:p>We also outline how these three tasks are tightly coupled, and how there exists a wide spectrum of solutions that either solve a particular task or jointly solve multiple tasks along with the interactions among them. To dissect the space of solutions, we introduce three main classification criteria, namely: (1) the type of constraints imposed by the user, (2) the type of dynamics considered in the embedding process, and (3) the allocation strategy adopted. Finally, we conclude with a few interesting research directions.</jats:p>

<jats:p>Trust management is one of the most challenging issues in the emerging cloud computing area. Over the past few years, many studies have proposed different techniques to address trust management issues. However, despite these past efforts, several trust management issues such as identification, privacy, personalization, integration, security, and scalability have been mostly neglected and need to be addressed before cloud computing can be fully embraced. In this article, we present an overview of the cloud service models and we survey the main techniques and research prototypes that efficiently support trust management of services in cloud environments. We present a generic analytical framework that assesses existing trust management research prototypes in cloud computing and relevant areas using a set of assessment criteria. Open research issues for trust management in cloud environments are also discussed.</jats:p>

<jats:p>Data stream mining is an active research area that has recently emerged to discover knowledge from large amounts of continuously generated data. In this context, several data stream clustering algorithms have been proposed to perform unsupervised learning. Nevertheless, data stream clustering imposes several challenges to be addressed, such as dealing with nonstationary, unbounded data that arrive in an online fashion. The intrinsic nature of stream data requires the development of algorithms capable of performing fast and incremental processing of data objects, suitably addressing time and memory limitations. In this article, we present a survey of data stream clustering algorithms, providing a thorough discussion of the main design components of state-of-the-art algorithms. In addition, this work addresses the temporal aspects involved in data stream clustering, and presents an overview of the usually employed experimental methodologies. A number of references are provided that describe applications of data stream clustering in different domains, such as network intrusion detection, sensor networks, and stock market analysis. Information regarding software packages and data repositories are also available for helping researchers and practitioners. Finally, some important issues and open questions that can be subject of future research are discussed.</jats:p>

<jats:p>The first steps in analyzing defensive malware are understanding what obfuscations are present in real-world malware binaries, how these obfuscations hinder analysis, and how they can be overcome. While some obfuscations have been reported independently, this survey consolidates the discussion while adding substantial depth and breadth to it. This survey also quantifies the relative prevalence of these obfuscations by using the Dyninst binary analysis and instrumentation tool that was recently extended for defensive malware analysis. The goal of this survey is to encourage analysts to focus on resolving the obfuscations that are most prevalent in real-world malware.</jats:p>

<jats:p>An efficient scheduling scheme is a crucial part of Wireless Mesh Networks (WMNs)—an emerging communication infrastructure solution for autonomy, scalability, higher throughput, lower delay metrics, energy efficiency, and other service-level guarantees. Distributed schedulers are preferred due to better scalability, smaller setup delays, smaller management overheads, no single point of failure, and for avoiding bottlenecks. Based on the sequence in which nodes access the shared medium, repetitiveness, and determinism, distributed schedulers that are supported by wireless mesh standards can be classified as either random, pseudo-random, or cyclic schemes. We performed qualitative and quantitative studies that show the strengths and weaknesses of each category, and how the schemes complement each other. We discuss how wireless standards with mesh definitions have evolved by incorporating and enhancing one or more of these schemes. Emerging trends and research problems remaining for future research also have been identified.</jats:p>

<jats:p> We introduce a unifying framework to provide the semantics of process algebras, including their quantitative variants useful for modeling quantitative aspects of behaviors. The unifying framework is then used to describe some of the most representative stochastic process algebras. This provides a general and clear support for an understanding of their similarities and differences. The framework is based on <jats:italic>State to Function Labeled Transition Systems</jats:italic> , F <jats:sc>u</jats:sc> TS <jats:sc>s</jats:sc> for short, that are state transition structures where each transition is a triple of the form ( <jats:italic>s</jats:italic> ,α,𝒫). The first and the second components are the source state, <jats:italic>s</jats:italic> , and the label, α, of the transition, while the third component is the <jats:italic>continuation function</jats:italic> , 𝒫, associating a value of a suitable type to each state <jats:italic>s</jats:italic> '. For example, in the case of stochastic process algebras the value of the <jats:italic>continuation function</jats:italic> on <jats:italic>s</jats:italic> ' represents the rate of the negative exponential distribution characterizing the duration/delay of the action performed to reach state <jats:italic>s</jats:italic> ' from <jats:italic>s</jats:italic> . We first provide the semantics of a simple formalism used to describe continuous-time Markov chains, then we model a number of process algebras that permit parallel composition of models according to the two main interaction paradigms (multiparty and one-to-one synchronization). Finally, we deal with formalisms where actions and rates are kept separate and address the issues related to the coexistence of stochastic, probabilistic, and nondeterministic behaviors. For each formalism, we establish the formal correspondence between the F <jats:sc>u</jats:sc> TS <jats:sc>s</jats:sc> semantics and its original semantics. </jats:p>

<jats:p>Software engineering evolved from a rigid process to a dynamic interplay of people (e.g., stakeholders or developers). Organizational and social literature call this interplay an Organizational Social Structure (OSS). Software practitioners still lack a systematic way to select, analyze, and support OSSs best fitting their problems (e.g., software development). We provide the state-of-the-art in OSSs, and discuss mechanisms to support OSS-related decisions in software engineering (e.g., choosing the OSS best fitting development scenarios). Our data supports two conclusions. First, software engineering focused on building software using project teams alone, yet these are one of thirteen OSS flavors from literature. Second, an emerging OSS should be further explored for software development: social networks. This article represents a first glimpse at OSS-aware software engineering, that is, to engineer software using OSSs best fit for the problem.</jats:p>