Changes in telecommunication services demand the development of a new infrastructure to attend new network applications' requirements. The traditional approach to network functions running over dedicated equipment can no longer handle all the dynamics of these new services. The network function virtualization (NFV) paradigm decouples a function from the underlying dedicated hardware thus making networks more flexible and agile. A set of virtual network functions (VNFs) can be deployed as virtual machines or containers across common servers, and orchestrated to compose a service function chain (SFC).Despite the many benefits of NFV, it raises several challenges. SFC placement is a complex task, since it requires taking into consideration the characteristics of VNFs, the SFC requirements, and the state of network infrastructure. This poses a challenge for large scale networks. Information regarding network resources are stored in a large database, and retrieving such data in order to perform SFC placement according to some strategy can be a problem. Limited memory capacity and the presence of a large number of disk operations can compromise the performance of SFC placement algorithms and make it unfeasible. In addition, the amount of memory available to run the allocation algorithm may not be sufficient to load the large amount of information that describe the network resources (occasionally in the hundreds of gigabytes). We address this problem by using a cluster based solution that stores and retrieves data for large scale infrastructures in order to perform SFC placement. The results demonstrate that the use of clusters in the preprocessing step can drastically reduce the size of the resulting database, as well as the execution time to select candidate nodes for a scalable SFC allocation.

With the emergence of new applications driven by the popularization of mobile devices, the next generation of mobile networks faces challenges to meet different requirements. Virtual Network Functions (VNFs) have been deployed to minimize operational costs and make network management more flexible. In this sense, strategies for VNF placement can impact different metrics of interest. Invoking and visiting VNFs in a specific execution order may be required for different use cases, resulting in a complete network service called Service Function Chain (SFC). The SFC placement problem is to define a feasible path in the physical infrastructure whose nodes and edges meet the computational and bandwidth requirements for the VNFs and virtual links, respectively. It has already been proved that this process is NP-hard and it is difficult to find an optimal solution to this problem. Therefore, in this paper, we propose the use of meta-heuristics to solve the SFC placement problem in cellular networks. We consider a triathlon competition leading to different mobility patterns. We collected real data about the competitors to simulate their movements through the scenario as well as the measured signal quality of the network. We formulate the SFC placement problem as a multi-objective problem where we try to minimize the placement cost and the total SFC delay. To solve the problem, we propose the use of two algorithms, NSGA-II and GDE3, which compare two different greedy approaches that prioritize the different optimization metrics considered in this work. Our results show that the meta-heuristics provide better results for each of the metrics. For all competition stages, GDE3 presented a slightly lower placement costs than NSGA-II, while NSGA-II had a lower delay in some scenarios.

O Direito Brasileiro tem feito uso de ferramentas tecnológicas a fim de melhorar a prestação jurídica e processual dos seus casos. Além disso, há ainda o uso da tecnologia no próprio escopo do trabalho dos operadores do Direito, dentre os quais se destacam a prova digital. Uma prova digital se refere a qualquer tipo de evidência ou informação que existe no formato eletrônico ou digital. Diante desse cenário, o presente estudo teve o objetivo de discorrer sobre o impacto que as provas digitais possuem na área trabalhistas. Buscou-se com essa temática, analisar de forma mais ampla, quais foram as mudanças positivas (ou não) que impactaram os operadores do Direito com o uso de provas digitais nos processos trabalhistas no Brasil. Na metodologia, tratou-se de uma revisão bibliográfica, baseada em estudos científicos selecionados e jurisprudência, cujo recorte temporal se deu entre 2018 a 2023 encontrados em base de dados tais como Scielo e Google Acadêmico. Nos resultados, a utilização de prova digital no Processo do Trabalho traz muitos pontos positivos, em especial, por se tratar de provas concretas e poderosas, baseadas em elementos técnicos e materiais mais confiáveis que as provas testemunhais. Apresenta, ainda, maior, proximidade com a verdade real no caso concreto, o que torna o resultado do processo mais justo para ambas as partes.

Introdução O prolapso retal é uma afecção relativamente rara, mais comum em mulheres acima dos 50 anos de idade. Pode ser oculto (quando não se exterioriza pelo ânus), incompleto (quando há prolapso apenas da mucosa) ou completo (prolapso de espessura total). Sua etiologia ainda não está bem definida. O tratamento do prolapso retal é cirúrgico, e existem diversas técnicas operatórias, seja por via perineal ou abdominal, e deve-se escolher a que mais se adequa ao paciente e à expertise do cirurgião, com taxa de recidiva considerável e variável a depender da técnica escolhida. A miíase compreende uma doença que pode classificada como externa, na forma cutânea, ou interna, nas formas intestinal e cavitária.

The network function virtualization (NFV) paradigm is an emerging technology that provides network flexibility by allowing the allocation of network functions over commodity hardware, like legacy servers in an IT infrastructure. In comparison with traditional network functions, implemented by dedicated hardware, the use of NFV reduces the operating and capital expenses and improves service deployment. In some scenarios, a complete network service can be composed of several functions, following a specific order, known as a service function chain (SFC). SFC placement is a complex task, already proved to be NP-hard. Moreover, in highly distributed scenarios, the network performance can also be impacted by other factors, such as traffic oscillations and high delays. Therefore, a given SFC placement strategy must be carefully developed to meet the network operator service constraints. In this paper, we present a systematic review of SFC placement advances in distributed scenarios. Differently from the current literature, we examine works over the last 10 years which addressed this problem while focusing on distributed scenarios. We then discuss the main scenarios where SFC placement has been deployed, as well as the several techniques used to create the placement strategies. We also present the main goals considered to create SFC placement strategies and highlight the metrics used to evaluate them.

SummaryA data center infrastructure is composed of heterogeneous resources divided into three main subsystems: IT (processor, memory, disk, network, etc.), power (generators, power transformers, uninterruptible power supplies, distribution units, among others), and cooling (water chillers, pipes, and cooling tower). This heterogeneity brings challenges for collecting and gathering data from several devices in the infrastructure. In addition, extracting relevant information is another challenge for data center managers. While seeking to improve the cloud availability, monitoring the entire infrastructure using a variety of (open source and/or commercial) advanced monitoring tools, such as Zabbix, Nagios, Prometheus, CloudWatch, AzureWatch, and others is required. It is often common to use many monitoring systems to collect real‐time data for data center components from different subsystems. Such an environment brings an inherent challenge stemming from the need to aggregate and organize the whole collected infrastructure data and measurements. This first step is necessary prior to obtaining any valuable insights for decision‐making. In this paper, we present the Data Center Availability (DCA) System, a software system that is able to aggregate and analyze data center measurements aimed toward the study of DCA. We also discuss the DCA implementation and illustrate its operation, monitoring a small University research laboratory data center. The DCA System is able to monitor different types of devices using the Zabbix tool, such as servers, switches, and power devices. The DCA System is able to automatically identify the failure time seasonality and trend present in the collected data from different devices of the data center.

With the popularity of mobile devices, the next generation of mobile networks has faced several challenges. Different applications have been emerged, with different requirements. Offering an infrastructure that meets different types of applications with specific requirements is one of these issues. In addition, due to user mobility, the traffic generated by the mobile devices in a specific location is not constant, making it difficult to reach the optimal resource allocation. In this context, network function virtualization (NFV) can be used to deploy the telecommunication stacks as virtual functions running on commodity hardware to meet users' requirements such as performance and availability. However, the deployment of virtual functions can be a complex task. To select the best placement strategy that reduces the resource usage, at the same time keeps the performance and availability of network functions is a complex task, already proven to be an NP-hard problem. Therefore, in this paper, we formulate the NFV placement as a multi-objective problem, where the risk associated with the placement and energy consumption are taken into consideration. We propose the usage of two optimization algorithms, NSGA-II and GDE3, to solve this problem. These algorithms were taken into consideration because both work with multi-objective problems and present good performance. We consider a triathlon circuit scenario based on real data from the Ironman route as an use case to evaluate and compare the algorithms. The results show that GDE3 is able to attend both objectives (minimize failure and minimize energy consumption), while the NSGA-II prioritizes energy consumption.

Objetivo Desenvolver um aplicativo móvel com informações para pacientes sobre seguimento pós-operatório das cirurgias colorretais.

Introdução: Relatar um caso de uma obstrução intestinal por Volvo de Ceco em um paciente tratado com colectomia direita e anastomose íleo-transverso término-lateral.

Traditional data center infrastructure suffers from a lack of standard and ubiquitous management solutions. Despite the achieved advances, existing tools lack interoperability and are sometimes hardware dependent. Vendors are already actively participating in the specification and design of new standard software and hardware interfaces within different forums. Nevertheless, the complexity and variety of data center infrastructure components that includes servers, cooling, networking, and power hardware, coupled with the introduction of the software defined data center paradigm, led to the parallel development of a myriad of standardization efforts. In an attempt to shed light on recent works, we survey and discuss the main standardization efforts for traditional data center infrastructure management.

With the continuous growth of the number of mobile devices connected to the Internet, cellular network infrastructure owners are facing several new challenges. The fifth generation of mobile technology (5G) is planned to enable a fully mobile and connected society and to empower socio-economic transformations. In 5G, different scenarios with high and strict requirements are being deployed. To deal with such heterogeneity, more advanced communication services are required. Network Function Virtualization (NFV) combined with distributed micro data centers (MDCs) can improve the management of the data flows through several 5G base stations. On the one hand, NFV provides high scalability without requiring significant architectural changes; and on the other hand, distributed MDCs decentralize architecture management, bringing the computational capabilities nearer to the base stations, hence reducing transmission delay. Nonetheless, the introduction of MDCs raises new points of failures in the architecture, impacting user experience. In this paper, we evaluate the impact of allocating MDCs to host base station functionalities; similarly, network functions run as virtual machines in the MDC, and their failures cannot be ignored. We consider a real footrace scenario as a case study. As packets are lost due to the high mobility of the runners and spectators we examine this metric. From simulations results, we discover that as the number of MDCs increases, the number of failures increases as well. However, the impact of each failure in terms of lost packets decreases considerably when considering scenarios with more MDCs. For example, by increasing the number of MDCs from one to seven, the failure impact in terms of lost packet drops by around 87.62%.

Making data centers highly available remains a challenge that must be considered since the design phase. The problem is selecting the right strategies and components for achieving this goal given a limited investment. Furthermore, data center designers currently lack reliable specialized tools to accomplish this task. In this paper, we disclose a formal method that chooses the components and strategies that optimize the availability of a data center while considering a given budget as a constraint. For that, we make use of stochastic models to represent a cloud data center infrastructure based on the TIA-942 standard. In order to improve the computational cost incurred to solve this optimization problem, we employ surrogate models to handle the complexity of the stochastic models. In this work, we use a Gaussian process to produce a surrogate model for a cloud data center infrastructure and we use three derivative-free optimization algorithms to explore the search space and to find optimal solutions. From the results, we observe that the Differential Evolution (DE) algorithm outperforms the other tested algorithms, since it achieves higher availability with a fair usage of the

SummaryNext‐generation cloud data centers are based on software‐defined data center infrastructures that promote flexibility, automation, optimization, and scalability. The Redfish standard and the Intel Rack Scale Design technology enable software‐defined infrastructure and disaggregate bare‐metal compute, storage, and networking resources into virtual pools to dynamically compose resources and create virtual performance‐optimized data centers (vPODs) tailored to workload‐specific demands. This article proposes four chassis design configurations based on Distributed Management Task Force's Redfish industry standard applied to compose vPOD systems, namely, a fully shared design, partially shared homogeneous design, partially shared heterogeneous design, and not shared design; their main difference is based on the used hardware disaggregation level. Furthermore, we propose models that combine reliability block diagram and stochastic Petri net modeling approaches to represent the complexity of the relationship between the pool of disaggregated hardware resources and their power and cooling sources in a vPOD. These four proposed design configurations were analyzed and compared in terms of availability and component's sensitivity indexes by scaling their configurations considering different data center infrastructure. From the obtained results, we can state that, in general, when one increases the hardware disaggregation, availability is improved. However, after a given point, the availability level of the fully shared, partially shared homogeneous, and partially shared heterogeneous configurations remain almost equal, while the not shared configuration is still able to improve its availability.

The number of connected devices and the amount of data traffic exchanged through mobile networks is expected to double in the near future. Long Term Evolution (LTE) and fifth generation (5G) technologies are evolving to support the increased volume, variety and velocity of data and new interfaces the Internet of Things demands. 5G goes beyond increasing data throughput, providing broader coverage and reliable ultra-low latency channels to support challenging future applications. However, this comes with a cost. As such, the architectural design of radio access network requires due consideration. This chapter explains why the radio access network is critical to 5G success and how novel trends on edge computing, network slicing and network virtualisation perform a critical role in optimising resources on emerging 5G infrastructures.

The development of protocols for mobile networks, especially for vehicular ad-hoc networks (VANETs), presents great challenges in terms of testing in real conditions. Using a production network for testing communication protocols may not be feasible, and the use of small networks does not meet the requirements for mobility and scale found in real networks. The alternative is to use simulators and emulators, but vehicular network simulators do not meet all the requirements for effective testing. Aspects closely linked to the behaviour of the network nodes (mobility, radio communication capabilities, etc.) are particularly important in mobile networks, where a delay tolerance capability is desired. This paper proposes a distributed emulator, EmuCD, where each network node is built in a container that consumes a data trace that defines the node’s mobility and connectivity in a real network (but also allowing the use of data from simulated networks). The emulated nodes interact directly with the container’s operating system, updating the network conditions at each step of the emulation. In this way, our emulator allows the development and testing of protocols, without any relation to the emulator, whose code is directly portable to any hardware without requiring changes or customizations. Using the facilities of our emulator, we tested InterPlanetary File System (IPFS), Sprinkler and BitTorrent content dissemination protocols with real mobility and connectivity data from a real vehicular network. The tests with a real VANET and with the emulator have shown that, under similar conditions, EmuCD performs closely to the real VANET, only lacking in the finer details that are extremely hard to emulate, such as varying loads in the hardware.

Introduction: Buschke-Löwenstein tumor is an uncommon variety of HPV infection. Being histologically benign, the tumor has invasive behavior. It may be associated with conditions of immunosupression, and recurrence after treatment is frequent. Objective: to describe a case in a patient with AIDS, to show that immunosupression is a contributing factor, and that surgery is the most effective treatment. Methods: a case description, with references in the literature. Results: extended resection surgery with satisfactory outcome in the postoperative period. Conclusion: surgery is the treatment recommended by most authors and biopsy is an indicative procedure to exclude malignancy.

The next-generation data center introduces the refactoring of the traditional data center in order to create pools of disaggregated resource units, such as processors, memory, storage, network, power, and cooling sources, named composable system (CSs) with the purpose of offering flexibility, automation, optimization, and scalability. In this paper, we solve an optimization problem to allocate CSs considering next- generation data centers. The main goal is to maximize the CS availability for the application owner, having its minimum requirements (in terms of CPU, memory, network and storage), and available budget as restrictions. This problem is modeled as a bounded multidimensional knapsack problem, and we solve it using Dynamic Programming (DP), and two Soft Computing approaches: Differential Evolution (DE) and Particle Swarm optimization (PSO). We consider two different scenarios in order to analyze heterogeneity and variability aspects when allocating CSs in a data center. Moreover, we also analyze the importance of system components to give directions and priorities of actions to upgrade the system design.

SummaryTo assess the availability of different data center configurations, understand the main root causes of data center failures and represent its low‐level details, such as subsystem's behavior and their interconnections, we have proposed, in previous works, a set of stochastic models to represent different data center architectures (considering three subsystems: power, cooling, and IT) based on the TIA‐942 standard. In this paper, we propose the Data Center Availability (DCAV), a web‐based software system to allow data center operators to evaluate the availability of their data center infrastructure through a friendly interface, without need of understanding the technical details of the stochastic models. DCAV offers an easy step‐by‐step interface to create and configure a data center model. The main goal of the DCAV system is to abstract low‐level details and modeling complexities, becoming the data center availability analysis a simple and less time‐consuming task.