Quality of Service Routing is at present an active and remarkable research area, since most emerging network services require specialized Quality of Service (QoS) functionalities that cannot be provided by the current QoS-unaware routing protocols. The provisioning of QoS based network services is in general terms an extremely complex problem, and a significant part of this complexity lies in the routing layer. Indeed, the problem of QoS Routing with multiple additive constraints is known to be NP-hard. Thus, a successful and wide deployment of the most novel network services demands that we thoroughly understand the essence of QoS Routing dynamics, and also that the proposed solutions to this complex problem should be indeed feasible and affordable. This article surveys the most important open issues in terms of QoS Routing, and also briefly presents some of the most compelling proposals and ongoing research efforts done both inside and outside the E-Next Community to address some of those issues.

Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services.

The rising number of mobile devices and their increasing computational capabilities enable new interactive context-sensitive applications. Popular examples are augmented reality games such as Google's Ingress, where users interact with each other in the real world while being part of the game at the same time. This local interaction pattern in the real world as well as in the game is not reflected in the underlying communication pattern. Every locally generated game event is first transferred to a backend server via a cellular connection, from where it is then further disseminated to all players within the given area of interest. This communiation pattern introduces significant delays and limits the interactivity of the game. In this work, we propose an event dissemination system that exploits the locality characteristics of mobile augmented reality games to (i) enable and configure local peer-to-peer dissemination of events when appropriate and (ii) reconfigure or replace the utilized peer-to-peer protocol to adapt to a wide range of requirements. Through extensive evaluation we show that the proposed system decreases the delivery delay by a factor of eight compared to the existing communication pattern, leading to significantly increased information accuracy.

Recent studies show that an increasing number of over-the-top live streams is delivered over the Internet. For the delivery of those streams, the dynamically changing and potentially large number of users imposes a major challenge. Flash crowds, where the number of users multiplies or significantly drops in a very small time frame, can cause serious degradations in the streaming performance. Due to the missing support for global network-layer multicast, overlay-based approaches have been broadly studied, showing that, with relaxed time constraints, they can scale well with the number of users. Yet, to support flash crowds, scaling has to happen quickly to keep up also with rapidly changing populations. Only a few approaches exist that focus on this aspect by influencing the streaming topology and, so far, it is not clear if and how these mechanisms can be applied to state-of-the-art hybrid streaming systems. Therefore, in this paper, TOPT is proposed, integrating new as well as existing mechanisms in a common framework. The evaluation shows that the streaming topology, indeed, plays a major role during flash crowds. The lightweight and decentralized tree-forming and topology optimization mechanisms of TOPT, combined with tracker extensions to attach new peers in batches, greatly help improving the streaming performance in terms of reduced playback interruptions by more than 60% and slight reduction in communication overhead at an acceptable increase in average startup delays by 24%.

The increasing capabilities of mobile communication devices are changing the way people interconnect today. Similar trends in the communication technology domain are leading to the expectation that data and media are available anytime and everywhere. A result is an increasing load on communication networks. In dynamic mobile networks that particularly rely on wireless communication such data requirements paired with environmental conditions like mobility or node density increase the risk of network failure. Consequently, monitoring is crucial in mobile networks to ensure reliable and efficient operation. Current monitoring mechanisms mostly rely on a static architecture and exhibit problems to handle the changes of mobile networks and environmental conditions over time. In this paper, an adaptive monitoring mechanism is presented to overcome these limitations. The mechanism exploits the connectivity and resource characteristics of mobile communication devices to (i) reconfigure its monitoring topology and (ii) adapt to changes of mobile networks and environmental conditions. Through evaluations we show that our proposed solution reduces the achieved relative monitoring error by a factor of six and represents a robust and reliable monitoring mechanism for these challenging environments.