En este trabajo proponemos una solución para la asignación de tareas en un entorno distribuido complejo y auto-organizado (sería el caso de las redes entre iguales o ́ P2P). Estamos interesados en las tareas que son comunes a todos los participantes o nodos del sistema. Cada uno de los nodos puede ejecutar estas tareas y, además, está interesado en que éstas se ejecuten. Cada nodo dispone de capacidad para la ejecución de cada una de las tareas. El coste para cada nodo es una información que no puede ser auditada y que es únicamente conocido por el nodo en cuestión. Suponemos que los nodos pueden mentir sobre su coste si eso les supone un beneficio; por ejemplo, por el ahorro que implicaría verse libre de ejecutar las tareas.

In this paper we explore the problem of achieving efficient packet transmission over unreliable links with worst case occurrence of errors. In such a setup, even an omniscient offline scheduling strategy cannot achieve stability of the packet queue, nor is it able to use up all the available bandwidth. Hence, an important first step is to identify an appropriate metric for measuring the efficiency of scheduling strategies in such a setting. To this end, we propose a relative throughput metric which corresponds to the long term competitive ratio of the algorithm with respect to the optimal. We then explore the impact of the error detection mechanism and feedback delay on our measure. We compare instantaneous error feedback with deferred error feedback that requires a faulty packet to be fully received in order to detect the error. We propose algorithms for worst-case adversarial and stochastic packet arrival models, and formally analyze their performance. The relative throughput achieved by these algorithms is shown to be close to optimal by deriving lower bounds on the relative throughput of the algorithms and almost matching upper bounds for any algorithm in the considered settings. Our collection of results demonstrates the potential of using instantaneous feedback to improve the performance of communication systems in adverse environments.

In this paper, we propose the use of prefix visibility at the interdomain level as an early symptom of anomalous events in the Internet. We focus on detecting anomalies which, despite their significant impact on the routing system, remain concealed from state of the art tools. We design a machine learning system to winnow the prefixes with unintended limited visibility – symptomatic of anomalous events – from the prefixes with intended limited visibility – resulting from legitimate routing operations.

To meet the increasing demand for wireless capacity, future networks are likely to consist of dense layouts of small cells. Thus, the number of concurrent users served by each base station (BS) is likely to be small which results in diminished gains from opportunistic scheduling, particularly under dynamic traffic loads. We propose user-initiated BS-transparent traffic spreading that leverages user-to-user communication to increase BS scheduling flexibility.

We consider Internet-based Master-Worker task computing systems, such as SETI@home, where a master sends tasks to potentially unreliable workers, and the workers execute and report back the result.

The IEEE Standard 802.3az, namely Energy Efficient Ether- net (EEE), has been recently introduced to reduce the power consumed in LANs. Since then, researchers have proposed various traffic shaping techniques to leverage EEE in order to boost power saving. In particular, packet coalescing is a promising mechanism which can be used on top of EEE to tradeoff power saving and packet delay.

The Czech Republic Embassy in Madrid in collaboration with the CzechTrade Center and IMDEA Networks Institute organize an event hosted...

In recent years, the volume of generated data has shown an exponential increase. New information and communication technologies, together with...

5TONIC Vice-President Arturo Azcorra delivered a talk entitled ‘Boosting 5G Research through Industry-Academic Partnerships’ at the MIT Media Lab. At this interdisciplinary research...