Predicting topology propagation messages in mobile ad hoc networks: The value of history

This research was funded by the Spanish Government under contracts TIN2016-77836-C2-1-R,TIN2016-77836-C2-2-R, and DPI2016-77415-R, and by the Generalitat de Catalunya as Consolidated ResearchGroups 2017-SGR-688 and 2017-SGR-990.The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40–55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.Peer ReviewedPostprint (published version

A low-cost and do-it-yourself device for pumping monitoring in deep aquifers

Water crises due to climate change, high population growth and increasing demands from industry and agriculture claim for increasing efficiency and universalizing water resources management strategies and techniques. Water monitoring helps providing necessary evidences for making sound decisions about managing water resources both now and in the future. In this work, a low cost and “do it yourself” communication device is proposed to record water production and energy consumption of electric pumpings from deep boreholes/wells, and to predict the impact of the ongoing and previous pumpings in the evolution of the water level in the aquifer. The proposal incorporates an edge-computing approach for the simulation of the aquifer response in real-time. Computation of results of interest is performed at the sensor, minimizing communication requirements and ensuring almost immediate results. An approximated solution to physically based modeling of aquifer response is computed thanks to the a priori expression of the water level time evolution in a reduced basis. The accuracy is enough to detect deviations from expected behaviour. The energy consumption of the device is very much reduced with respect to that of a full modelling, which can be computed off-line for calibrating reduced model parameters and perform detailed analyses. The device is tested in a real scenario, in a mountain subbasin of the Ebro river in Spain, obtaining a good trade-off between performance, price, and energy consumption.This research has been partly supported by EU under grant agreement N. 825184 and funded by the Government of Spain under contracts PID2019-106774RB-C21, PID2019-106774RB-C22, and PID2020-113172RB-I00 and by the Government of Catalonia as Consolidated Research Groups 2017-SGR-688 and 2017-SGR-990, and Pre-consolidated Research Group 2017-SGR-1496. The APC was funded by the Open program from Universitat Rovira i Virgili.Peer ReviewedPostprint (published version

Minimulticomputador de bajo coste

En la mayoría de los estudios de Grado en Ingeniería Informática hay asignaturas que abordan el tema de la supercomputación. Uno de sus objetivos es adquirir competencias en programación paralela. Para realizar ejercicios y prácticas se suelen usar estándares como OpenMP, MPI y CUDA. Para programar con dichos estándares se usan sistemas de elevado precio, lo que hace que el presupuesto disponible limite el número de procesadores. Por lo tanto, el acceso a un supercomputador con cientos de procesadores (que supone centenares de miles de euros) no parece estar justificado para realizar prácticas con los estudiantes. Sin embargo, y siguiendo la tendencia de usar muchos procesadores pero poco potentes basados en ARM, se puede construir un minimulticomputador de bajo coste por un precio equivalente a un servidor de memoria compartida. Este trabajo presenta un recurso docente basado en placas de HardKernel, que integran 64 placas Odroid y que mediante Gigabit-Ethernet permiten montar un servidor de programación MPI con 256 procesadores. Si bien se trata de un recurso de bajas prestaciones, es interesante el hecho de tener acceso a centenares de procesadores para poder hacer estudios de escalabilidad, manteniendo un buen compromiso entre prestaciones, precio y consumo.Este trabajo ha contado con la financiación del Gobierno de España bajo los contratos TIN2016-77836-C2-1-R, TIN2016-77836-C2-2-R, TIN2016-75344-R y DPI2016-77415-R, y también de la Generalitat de Catalunya como Grupos de Investigación Consolidados 2017-SGR-688 y 2017-SGR-990Peer ReviewedPostprint (published version

Carcass and Meat Quality Traits in an Embden×Toulouse Goose Cross Raised in Organic Dehesa

his study assessed the influence of genetic type (Embden-Anser anser, EE; Toulouse-Anser anser, TT and F1 cross, ET) for meat characteristics (carcass, meat quality and fatty acid (FA) profiles), of domestic geese “Anser anser domesticus” raised in dehesa as an alternative, organic feeding system. Carcass and breast muscle weight (p<0.01) were greater for the ET group at the same live weight. None of the groups showed differences in the production of fatty liver with this type of feeding. Higher values were found for maximum Warner–Bratzler shear force (between 7.62 and 8.87 kg/cm2), which implies the improvement of this parameter. High levels of oleic FAs were obtained, especially for the TT group. The polyunsaturated/saturated FA ratio was highest for the ET group (p<0.001), reflecting the optimum nutritional values as a component of a healthy consumer die

Time series analysis to predict link quality of wireless community networks

Community networks have emerged under the mottosCommunity networks have emerged under the mottos “break the strings that are limiting you”, “don't buy the network, be the network” or “a free net for everyone is possible”. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed, and decentralized networks. We demonstrate that it is possible to accurately predict the link quality in 98% of the instances, both in the short and the long terms. Particularly, we analyse the behaviour of the links globally to identify the best prediction algorithm and metric, the impact of lag windows in the results, the prediction accuracy some time steps ahead into the future, the degradation of prediction over time, and the correlation of prediction with topological features. Moreover, we also analyse the behaviour of links individually to identify the variability of link quality prediction between links, and the variability of link quality prediction over time. Finally, we also present an optimized prediction method that considers the knowledge about the expected link quality values.Peer ReviewedPostprint (author's final draft

Discurso econômico e política colonial no império Luso-Brasileiro (1750-1808)

O artigo reflete sobre a ação política do marquês de Pombal e de Dom Rodrigo de Souza Coutinho, comparando o conjunto de suas orientações no campo econômico e colocando em perspectiva a questão geral do reformismo ilustrado no mundo ibérico. A ambição geral é a discussão de diferentes percursos no plano da história das ideias no século XVIII, mapeando o quadro de influências ao discurso econômico e político dedicado à concepção e execução das reformas, com destaque para a preocupação com o papel das colônias (o Brasil, essencialmente) na dinâmica econômica portuguesa ao longo da segunda metade do século XVIII

Using a history-based approach to predict topology control information in mobile ad hoc networks

Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.Peer ReviewedPostprint (published version

Using a history-based approach to predict topology control information in mobile ad hoc networks

Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.Peer Reviewe

A low-cost multicomputer for teaching environments

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksWe propose a teaching resource that uses Hard Kernel boards to build an MPI server with 256 cores. Although this system has a relatively low performance, the aim is to provide access to hundreds of cores for carrying out scalability analyses, while obtaining a good trade-off between performance, price, and energy consumption. Here, we give details about the implementation of this system at both the hardware and software levels. We also explain how it was used to teach parallel programming in a university degree course, and discuss the teachers’ and students’ comments about using this new system.This work has been funded by the Government of Spain undercontractsTIN2016-77836-C2-1-R, TIN2016-77836-C2-2-R,TIN2016-75344-R and DPI2016-77415-R, and by the Governmentof Catalonia as Consolidated Research Groups 2017-SGR-688 and 2017-SGR-990Peer ReviewedPostprint (published version

Time series analysis to predict end-to-end quality of wireless community networks

Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.Peer Reviewe