Abstract
ReFlO is a framework and interactive tool to record and systematize domain knowledge used by experts to derive complex pipe-and-filter (PnF) applications. Domain knowledge is encoded as transformations that alter PnF graphs by refinement (adding more details), flattening (removing modular boundaries), and optimization (substituting inefficient PnF graphs with more efficient ones). All three kinds of transformations arise in reverse-engineering legacy PnF applications. We present the conceptual foundation and tool capabilities of ReFlO, illustrate how parallel PnF applications are designed and generated, and howdomain-specific libraries of transformations are developed.

Abstract

Abstract
A common problem in networking research and development is the duplicate effort of writing simulation and implementation code of network protocols. This duplication can be avoided through the use of fast prototyping development processes, which enable reusing simulation code in real prototyping and in production environments. Although this functionality is already available by using ns-3 emulation, there are still limitations regarding the additional packet processing that emulation introduces, which degrades the node’s performance and limits the amount of network traffic that can be processed. In this paper we propose an approach to reduce the performance problem associated with fast prototyping that consists in migrating data plane operations processing to outside of ns-3. In a well-designed network, most of the traffic should be data. By moving the data plane operations outside of ns-3 the overhead associated with this kind of traffic is greatly reduced, while control plane protocols may still be reused. In order to validate our proposed solution, we extended the Wireless Metropolitan Routing Protocol (WMRP) and Optimized Link State Routing (OLSR) protocols to use the developed architecture, tested their performance in real environments, and verified the amount of code reuse between the simulator and the real system.

Abstract
In this paper, we analyse the impact of spring temperature (ST) and soil water (SW) on wine production volume (WPV) for the period 1933 to 2013 in the Douro region. We employ a state-space regression model to capture possible structural changes in wine production caused by a change in ST and/or SW. We find that the ST explains about 65 % of the variability of WPV. In contrast, the summer SW level increases the R (adj)-square to 83 % and the Akaike criterion value was lower. We also find interesting dynamic properties of SW and ST. The immediate impact of an increase in SW is negative for WPV, while the SW that is in the ground, i.e. from the previous 2 and 3 years, have a positive effect on actual WPV. Moreover, the individual changes of ST and SW have similar dynamic impact on WPV. Our main finding is that climate change does not only change the variables in question but also the winegrape vineyards adding to the negative impact on WPV levels. As a result we observe a shift of the relative importance away from ST to SW.

Abstract
The massification of mobile access and services has increased the demand for faster, reliable and ubiquitous networks, which has been leading to additional pressure on satellite service providers to provide larger throughput. This inherently raises the challenge of bandwidth management. Regulatory activities have led to frequency allocation charts that are growing more complex and harder to manage. Such problem needs therefore to be addressed in order to achieve a more efficient use of resources and cope with the escalating traffic in satellite communications in the sub-5GHz bands. The H2020 SCREEN project is addressing this challenge by resorting to cognitive radio (CR) technology at S-band. SCREEN is working towards maturing several CR enabling technologies up to TRL4/5, considering two reference scenarios: Satcom-enabled UAV constellations and Inter-Satellite Links for satellite networks. This paper focuses on the design, development, simulation and implementation of the proposed cognitive radio algorithms in SCREEN, namely spectrum sensing, dynamic spectrum manager (DSM), and learning techniques, presenting the most promising results achieved thus far. In CR environments, communication conditions may show a considerable variability, and therefore, adaptable and reconfigurable spectrum sensing architectures can bring valuable benefits. In this paper, we describe a multi-resolution spectrum sensing architecture, compatible with the proposed approach for dynamic spectrum management, which considers a local and a global DSM and how to combine both methods to offer a higher level of performance. Regarding learning techniques, SCREEN defined two principal strategies: Centralized learning and de-centralized learning that lend themselves to different protocol architectures, namely in terms of medium-access control. Additionally, a novel simulation framework for evaluating cognitive radio for Satcom applications is presented, which is based on the open source network simulator (ns-3). The simulator considers realistic satellite orbits, propagation loss and propagation delay models and supports the placement of interferer nodes. The simulation results are output in the open KMZ format, allowing visualization in Google Earth and other GIS. The integrated simulation tool is one of the major novelties of SCREEN. Simulation results and implications are presented on the comparison of both centralized and decentralized MAC approaches with different learning and channel assignment strategies, e.g. based on greedy or reinforcement learning. Finally, early implementation results of these algorithms in an off-the-shelf space Software-Defined Radio platform will be discussed, as a pioneer step into showing the true applicability of cognitive radio for a new generation of flexible and versatile space-bound transceivers. Copyright

Abstract
Large food retailers have to deal with a complex distribution network with multiple distribution centres, different temperature requirements, and a vast range of store formats. This project used an optimization-simulation approach to help food retailer Sonae MC make the best decisions regarding product-warehouse-outlet assignment, product delivery modes planning and fleet sizing.