The edge, the fog, the cloud, and even the end-user's devices play a key role in the management of the health sensitive content/data lifecycle. However, the creation and management of solutions including multiple applications executed by multiple users in multiple environments (edge, the fog, and the cloud) to process multiple health repositories that, at the same time, fulfilling non-functional requirements (NFRs) represents a complex challenge for health care organizations. This paper presents the design, development, and implementation of an architectural model to create, on-demand, edge-fog-cloud processing structures to continuously handle big health data and, at the same time, to execute services for fulfilling NFRs. In this model, constructive and modular blocks, implemented as microservices and nanoservices, are recursively interconnected to create edge-fog-cloud processing structures as infrastructureagnostic services. Continuity schemes create dataflows through the blocks of edge-fog-cloud structures and enforce, in an implicit manner, the fulfillment of NFRs for data arriving and departing to/from each block of each edge-fog-cloud structure. To show the feasibility of this model, a prototype was built using this model, which was evaluated in a case study based on the processing of health data for supporting critical decision-making procedures in remote patient monitoring. This study considered scenarios where end-users and medical staff received insights discovered when processing electrocardiograms (ECGs) produced by sensors in wireless IoT devices as well as where physicians received patient records (spirometry studies, ECGs and tomography images) and warnings raised when online analyzing and identifying anomalies in the analyzed ECG data. A scenario where organizations manage multiple simultaneous each edge-fog-cloud structure for processing of health data and contents delivered to internal and external staff was also studied. The evaluation of these scenarios showed the feasibility of applying this model to the building of solutions interconnecting multiple services/applications managing big health data through different environments. INDEX TERMS Big health data, edge-fog-cloud, health-IoT processing, Internet of Things, microservice architecture.

In this work, a sensor in microstrip technology and a methodology for measuring the real part and the imaginary part of the complex uniaxial permittivity of solid anisotropic samples are presented. The sensor is based on a pair of parallel lines coupled resonators and a cleft arranged in the coupling region which allows to hold the samples under test (SUTs). The proposed methodology relates the change in the even/odd resonance frequency with the real part of the permittivity in the vertical/horizontal direction, and the change in the Q factor of the even/odd mode with the imaginary part of the permittivity in the vertical/horizontal direction. The methodology was successfully verified with the characterization, at 2.43 GHz of anisotropic samples of printed PLA, Diclad 880, and RO4350B using the knowns materials: RT5870, PTFE and RO4003.

The topic of spectral line suppression is of major importance when designing impulse radio ultrawideband (IR-UWB) systems. The presence of spectral lines in the power spectral density (PSD) may limit the maximum transmission power to comply with UWB regulations, thus, affecting the system performance. Although previous works have shown the advantages of IR-UWB over fiber (UWBoF) implementations, the topic of spectral line suppression in PSD in such systems has not been entirely addressed. This letter proposes a simple IR-UWBoF system using spectral line free (SLF) convolutional codes to address this topic. Experimental results show that the proposed system offers improved PSD characteristics compared to conventional IR-UWBoF implementations. Furthermore, it is demonstrated that the proposed system is able to deliver SLF IR-UWB signals over single-mode fibers up to 30 km.ABSTRACT: This article presents a novel active W-band phase shifter implemented using IHP SiGe Heterojunction Bipolar Transistor (HBT) 0.25-mm SG25H1 technology with three vector (0 -120 -240 ) sum technique. The integrated chip consists of a 3-way Wilkinson power divider/ combiner with 0 -120 -240 phase shifting lines and three low-noise amplifiers (LNA) working at 77 GHz, which comprises a total of 1.5 3 Figure 5 Degradation of SFL convolutionally coded Q-BOPPM TH-IR UWB signals after the fiber transmission: (a) MATLAB signal; (b) as measured at point A in Figure 3; (c) as measured in B2B configuration at point B in Figure 3; (d) as measured after 20-km SMF transmission; and (e) as measured after 30-km SMF transmission. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com]

Multi-unmanned aerial vehicle (multi-UAV) systems have become popular in applications such as precision agriculture, remote sensing, and pollution monitoring. Commonly, multi-UAV systems require to reach and maintain a specific flight formation during mission execution. This can be achieved by using a distributed UAV formation control strategy in which each UAV has a flight controller whose function is to calculate the control actions for the UAV actuators such that the UAV formation is maintained. To perform this task, the control strategy requires the reliable and timely exchange of information within the UAV formation. The information that is needed by the controller is commonly referred to as state information (SI). It has been assumed that SI can be properly disseminated by means of multi-hop communications, i.e., by deploying a flying ad-hoc network (FANET). In this sense, multi-hop broadcast protocols (MBPs) that were previously proposed for mobile and vehicular ad-hoc networks seem to be suited for this task. However, previous work dealing with distributed UAV formation control has made communication and networking assumptions that would be hard to fulfill in actual FANET deployments. Moreover, the efficiency of the MBPs to disseminate SI within a FANET remains unexplored. The goal of this paper is to analyze how the network performance offered by different MBPs impacts the effectiveness of distributed UAV formation control to maintain UAV formation. An evaluation framework to perform this task is proposed in this paper. The simulation results demonstrate the relevance of MBP performance in SI message dissemination and thus in the ability of the controller to maintain a formation.