Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user's perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the “health” of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner.

As the IoT adoption is growing in several fields, cybersecurity attacks involving low-cost end-user devices are increasing accordingly, undermining the expected deployment of IoT solutions in a broad range of scenarios. To address this challenge, emerging Network Function Virtualization (NFV) and Software Defined Networking (SDN) technologies can introduce new security enablers, thereby endowing IoT systems and networks with higher degree of scalability and flexibility required to cope with the security of massive IoT deployments. In this sense, honeynets can be enhanced with SDN and NFV support, to be applied into IoT scenarios thereby strengthening the overall security. IoT honeynets are virtualized services simulating real IoT networks deployments, so that attackers can be distracted from the real target. In this paper, we present a novel mechanism leveraging SDN and NFV aimed to autonomously deploy and enforce IoT honeynets. The system follows a security policy-based approach that facilitates management, enforcement and orchestration of the honeynets and it has been successfully implemented and tested in the scope of H2020 EU project ANASTACIA, showing its feasibility to mitigate cyber-attacks.

This paper presents a novel monitoring architecture addressed to the cloud provider and the cloud consumers. This architecture offers a monitoring platform-as-a-Service to each cloud consumer that allows to customize the monitoring metrics. The cloud provider sees a complete overview of the infrastructure whereas the cloud consumer sees automatically her cloud resources and can define other resources or services to be monitored. This is accomplished by means of an adaptive distributed monitoring architecture automatically deployed in the cloud infrastructure. This architecture has been implemented and released under GPL license to the community as “MonPaaS”, open source software for integrating Nagios and OpenStack. An intensive empirical evaluation of performance and scalability have been done using a real deployment of a cloud computing infrastructure in which more than 3,700 VMs have been executed.

Much of the research into language learners' use of corpus resources has been conducted by means of indirect observation methodologies, like questionnaires or self-reports. While this type of study provides an excellent opportunity to reflect on the benefits and limitations of using corpora to teach and learn language, the use of indirect observation methodologies may confine the scope of research to learners' opinions about the benefits of using corpora for language learning and their self-perceived difficulties in consulting them. This article proposes and discusses the use of logs to research learners' actual use of corpus-based resources, analyzing the number of events or actions performed by each individual, the total number of different web services used, the number of activities completed, the number of searches performed on the British National Corpus (BNC) and, last, the number of words or wildcards per BNC search. Our research used these parameters to investigate whether learner interaction with corpus-based resources differed under different corpus consultation conditions: guided versus non-guided consultation. Our findings show that the individuals in the two research conditions behaved differently in two of the parameters analyzed: the number of different web services used during the completion of the tasks and the number of BNC searches. Our results corroborate empirically the suggestions found in the literature that skills and guidance are necessary when teachers take a corpus to the classroom. Similarly, we offer evidence that user tracking is essential to claim research and results validity.

Using wireless sensor network (WSN) for building new sensing and actuating applications in space and extreme environments (SEEs) can fuel a new application paradigm if it can be adopted into a new strategy. This complementary contribution from the Guest Editors carries an important message of breaking away from conventional WSN research and developments and adopting a heterogeneous agile unconventional wireless sensing (UWS) approach deployment. For this, we urge the use of lightweight WSN known as wireless sensor systems (WSS) to develop optimized solutions for SEE. This paper also discusses some critical technologies of WSS-SEE and includes three key aspects of a new approach to examine: 1) the characterizes of SEE; 2) potential applications of UWS; and 3) heterogeneously nature of the applications. A further clarification for deployment of UWS is demonstrated using a table with six groups of typical application areas from the recent publications media.