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Background Health care professionals have to judge the appropriateness of treatment in critical care on a daily basis. There is general consensus that critical care interventions should not be performed when they are inappropriate. It is not yet clear which chances of survival are considered necessary or which risk for serious disabilities is acceptable in quantitative terms for different stakeholders to start intensive care treatment. Methods We performed an anonymous online survey in a random sample of 1,052 participants recruited via email invitation and social media. Age, sex, nationality, education, professional involvement in health care, critical care medicine and treatment decisions in critical care medicine as well as personal experience with critical illness were assessed as potential influencing variables. Participants provided their opinion on the necessary chances of survival and the acceptable risk for serious disabilities to start a high-risk or uncomfortable therapy for themselves, relatives or for their patients on a scale of 0–100%. Results Answers ranged from 0 to 100% for all questions. A three-peak pattern with different distributions of the peaks was observed. Sex, education, being a health care professional, being involved in treatment decisions and religiosity influence these opinions. Male respondents and those with a university education would agree that a risky and uncomfortable treatment should be started even with a low chance of survival for themselves, relatives and patients. More respondents would choose a lower necessary chance of survival (0–33% survival) when deciding for patients compared to themselves or relatives to start a risky and uncomfortable treatment. On the other hand, the majority of respondents would accept only a low risk of severe disability for both themselves and their patients. Conclusion No cut-off can be identified for the necessary chances of survival or the acceptable risk of disability to help quantify the “inappropriateness” of critical care treatment. Sex and education are the strongest influencing factors on this opinion. The large variation in personal opinions, depending on demographic and personality variables and education needs to be considered in the communication between health care professionals and patients or surrogates.

Importance Morbidity is still high in pancreatic surgery, driven mainly by gastrointestinal complications such as pancreatic fistula. Perioperative thoracic epidural analgesia (EDA) and patient-controlled intravenous analgesia (PCIA) are frequently used for pain control after pancreatic surgery. Evidence from a post hoc analysis suggests that PCIA is associated with fewer gastrointestinal complications. Objective To determine whether postoperative PCIA decreases the occurrence of gastrointestinal complications after pancreatic surgery compared with EDA. Design, Setting, and Participants In this adaptive, pragmatic, international, multicenter, superiority randomized clinical trial conducted from June 30, 2015, to October 1, 2017, 371 patients at 9 European pancreatic surgery centers who were scheduled for elective pancreatoduodenectomy were randomized to receive PCIA (n = 185) or EDA (n = 186); 248 patients (124 in each group) were analyzed. Data were analyzed from February 22 to April 25, 2019, using modified intention to treat and per protocol. Interventions Patients in the PCIA group received general anesthesia and postoperative PCIA with intravenous opioids with the help of a patient-controlled analgesia device. In the EDA group, patients received general anesthesia and intraoperative and postoperative EDA. Main Outcomes and Measures The primary end point was a composite of pancreatic fistula, bile leakage, delayed gastric emptying, gastrointestinal bleeding, or postoperative ileus within 30 days after surgery. Secondary end points included 30-day mortality, other complications, postoperative pain levels, intraoperative or postoperative use of vasopressor therapy, and fluid substitution. Results Among the 248 patients analyzed (147 men; mean [SD] age, 64.9 [10.7] years), the primary composite end point did not differ between the PCIA group (61 [49.2%]) and EDA group (57 [46.0%]) (odds ratio, 1.17; 95% CI, 0.71-1.95P = .54). Neither individual components of the primary end point nor 30-day mortality, postoperative pain levels, or intraoperative and postoperative substitution of fluids differed significantly between groups. Patients receiving EDA gained more weight by postoperative day 4 than patients receiving PCIA (mean [SD], 4.6 [3.8] vs 3.4 [3.6] kg;P = .03) and received more vasopressors (46 [37.1%] vs 31 [25.0%];P = .04). Failure of EDA occurred in 23 patients (18.5%). Conclusions and Relevance This study found that the choice between PCIA and EDA for pain control after pancreatic surgery should not be based on concerns regarding gastrointestinal complications because the 2 procedures are comparable with regard to effectiveness and safety. However, EDA was associated with several shortcomings. Trial Registration German Clinical Trials Register:DRKS00007784

Virtual reality has been gaining popularity in recent years fueled by the proliferation of affordable consumer-grade devices such as Oculus Rift, HTC Vive, and Samsung VR. Amongst the various VR applications, 360° video streaming is currently one of the most popular ones. However, it poses a series of challenges to the serving content distribution systems. One challenge is the significantly increased bandwidth requirement for streaming such content in real time. Recent research has shown that only streaming the content that is in the user's (field-of-view) FoV in high quality can lead to strong bandwidth savings. This can be achieved by analyzing the viewers head orientation and movement based on sensor information. Alternatively, historic information from users that watched the content in the past can be considered to prefetch 360° video data in high quality assuming the viewer will direct the FoV to these areas. This paper presents a 360° video streaming system that transitions between sensor- and content-based predictive mechanisms. We evaluate the effects of our system on the Quality of Experience (QoE) of such a VR streaming system and show that the perceived quality can be increased between 50% and 80% compared to systems that only apply either one of the two approaches.

State-of-the-art software-defined wide area networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work, we design, implement, and evaluate a novel architecture (denoted as SABR) that leverages the benefits of software-defined networking (SDN) to provide network-assisted adaptive bitrate streaming. With clients retaining full control of their streaming algorithms, we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of quality of experience (QoE) and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer’s QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of content delivery network caches. Backed by our study of SDN-assisted streaming, we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well-established player algorithms. We evaluate SABR together with state-of-the-art dynamic adaptive streaming over HTTP (DASH) quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. In addition, we compare the performance of different caching strategies in combination with SABR. Our trace-based measurements show the substantial improvement in cache hit rates and QoE metrics in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for adaptive bitrate video streaming applications.

The proliferation of cloud data center applications and network function virtualization (NFV) boosts dynamic and QoS dependent traffic into the data centers network. Currently, lots of network routing protocols are requirement agnostic, while other QoS-aware protocols are computationally complex and inefficient for small flows. In this paper, a computationally efficient congestion avoidance scheme, called CECT, for software-defined cloud data centers is proposed. The proposed algorithm, CECT, not only minimizes network congestion but also reallocates the resources based on the flow requirements. To this end, we use a routing architecture to reconfigure the network resources triggered by two events: (1) the elapsing of a predefined time interval, or, (2) the occurrence of congestion. Moreover, a forwarding table entries compression technique is used to reduce the computational complexity of CECT. In this way, we mathematically formulate an optimization problem and define a genetic algorithm to solve the proposed optimization problem. We test the proposed algorithm on real-world network traffic. Our results show that CECT is computationally fast and the solution is feasible in all cases. In order to evaluate our algorithm in term of throughput, CECT is compared with ECMP (where the shortest path algorithm is used as the cost function). Simulation results confirm that the throughput obtained by running CECT is improved up to 3× compared to ECMP while packet loss is decreased up to 2×.

The current body of research on Dynamic Adaptive Streaming over HTTP (DASH) contributes various adaptation algorithms aiming to optimize performance metrics such as the Quality of Experience. Intuitively, the heterogeneity of the streaming environment and the underlying technologies lead many of the developed approaches to possess clear performance affinities denoted here as sweet spots. We observe, however, that systematic comparisons of these algorithms are usually conducted within homogeneous player environments. In this work, we show the substantial impact of player choice and configuration on the streaming performance. To this end, we systematically examine three established open-source DASH players, i.e., DASH.JS, Google's Shaka Player, and AStream, that implement fundamentally different configurations featuring various adaptation algorithms. By establishing a large scale emulation framework we (i) extract player sweet spots and (ii) achieve a direct, reproducible comparison of real-world DASH players and algorithms. We present empirical evidence demonstrating that an isolated analysis of DASH player modules is insufficient to capture the player streaming performance. One of the major observations is that the choice of the target buffer size together with the player implementation dominates the choice of the adaptation algorithms.

State-of-the-art Software Defined Wide Area Networks (SD-WANs) provide the foundation for flexible and highly resilient networking. In this work we design, implement and evaluate a novel architecture (denoted SABR) that leverages the benefits of SDN to provide network assisted Adaptive Bitrate Streaming. With clients retaining full control of their streaming algorithms we clearly show that by this network assistance, both the clients and the content providers benefit significantly in terms of QoE and content origin offloading. SABR utilizes information on available bandwidths per link and network cache contents to guide video streaming clients with the goal of improving the viewer's QoE. In addition, SABR uses SDN capabilities to dynamically program flows to optimize the utilization of CDN caches.; AB@Backed by our study of SDN assisted streaming we discuss the change in the requirements for network-to-player APIs that enables flexible video streaming. We illustrate the difficulty of the problem and the impact of SDN-assisted streaming on QoE metrics using various well established player algorithms. We evaluate SABR together with state-of-the-art DASH quality adaptation algorithms through a series of experiments performed on a real-world, SDN-enabled testbed network with minimal modifications to an existing DASH client. Our measurements show the substantial improvement in cache hitrates in conjunction with SABR indicating a rich design space for jointly optimized SDN-assisted caching architectures for video streaming applications.

In this work we outline a framework for measurement-based performance evaluation in SDN environments. The SDN paradigm, which is based on a strict separation of the network logic from the underlying physical substrate, necessitates a comprehensive global view of the network state. To augment the network representation, we propose mechanisms for extracting traffic characteristics from network observations which are used to derive performance metrics. Such metrics can be exploited by SDN applications to optimize the performance of SDN services. Given the bursty nature of network traffic and the well known adverse impact of this property on network performance, we propose an approach for extracting flow autocorrelations from switch counters. Our main contribution is a random sampling approach that reduces the monitoring overhead while enabling a fine grained characterization of the flow autocorrelation structure. We analytically evaluate the impact of random sampling and demonstrate how services may use the estimated traffic properties to compute useful performance metrics.

International audience; Sensor networks are prone to congestion due to bursty and high-bandwidth data traffic, combined with wireless links and many-to-one data routing to a sink. Delayed and dropped packets then degrade the performance of the sensing application. In this paper, we investigate the value of separate handling of sensor control and data traffic, during times of congestion, in a closed-loop sensor network. We first show that prioritizing sensor control traffic over data traffic decreases the round-trip control-loop delay, and consequently increases the quantity and quality of the data collected by the sensor network. We then ground our analysis in a closed-loop meteorological sensor network, focusing on a storm-tracking application running over a network of X-band radars. Our application measures reflectivity (a measure of the number of scatterers in a unit volume of atmosphere known as a voxel) and tracks storms (i.e., regions of high reflectivity) using a Kalman filter. Considering data quantity, we show that prioritizing sensor control traffic increases the number of voxels, V, that can be scanned given a constant number of reflectivity samples, Nc, obtained per voxel. Here, utility increases linearly with the number of scanned voxels. Considering data quality, we show that prioritizing sensor control traffic increases the number of reflectivity samples, N, that can be obtained per voxel given a constant number of voxels, Vc, to scan. Here, since sensing accuracy improves only as a function of radicN, the gain in accuracy for the reflectivity estimate per voxel as N increases is relatively small except when prioritizing sensor control increases N significantly (such as when sensor control packets suffer severe delays). Because accuracy also degrades as a function of radicN, however, and because prioritizing sensor control traffic reduces the number of control packets dropped, data degradation is mitigated. Considering the performance of the tracking application, we then show that during times of severe congestion, not prioritizing sensor control can actually lead to tracking errors accumulating over time.

A lot of attention has been given to multihop wireless networks lately, but further research—in particular, through experimentation—is needed. This attention has motivated an increase in the number of 802.11-based deployments, both indoor and outdoor. These testbeds, which require a significant amount of resources during both deployment and maintenance, are used to run measurements in order to analyze and understand the limitation and differences between analytical or simulation-based figures and the results from real-life experimentation. This paper makes two major contributions: (i) first, we describe a novel wireless multihop testbed, which we name FloorNet, that is deployed and operated under the false floor of a lab in our Computer Science building. This false floor provides a strong physical protection that prevents disconnections or misplacements, as well as radio shielding (to some extent) thanks to the false floor panels—this later feature is assessed through experimentation; (ii) second, by running exhaustive and controlled experiments we are able to analyze the performance limits of commercial off-theshelf hardware, as well as to derive practical design criteria for the deployment and configuration of mesh networks. These results both provide valuable insights of wireless multihop performance and prove that FloorNet constitutes a valuable asset to research on wireless mesh networks. European Community's Seventh Framework Program Publicado

International audience; In October 2011 a new, ambitious project was launched, named FIBRE (Future Internet testbeds experimentation between Brazil and Europe). Its main goal is to create common space between Brazil and EU for Future Internet experimental research into network infrastructure and distributed applications, by building and operating a federated EU-Brazil Future Internet experimental facility. Apart from bridging partners from two continents, the project brings together different technologies, including OpenFlow, wireless and optical communications. To demonstrate the public utility of the facility, FIBRE will design and implement a set of pilot applications ranging from seamless wireless connectivity to high-definition content delivery. The poster to be presented describes FIBRE’s goals, its testbed facilities and a schema of the envisioned architecture embracing the functionalities of the individual testbeds, as well as their federation. This schema has resulted from the collaborative work of the partners in order to define the functional requirements related to such an architecture. Our ambition with this poster is to attract new users for the facility from the experimental research community, but also to stimulate interest for FIBRE’s activities among the conference’s attendees.