Information and communication technologies (ICTs) often fail to perform well in environments and scenarios that were not envisioned at the time of the ICTs creation. Examples of such failures include poor usability of traditional WiFi networks in resource-constrained rural areas, geographically-dependent performance of centralised networked systems, and context-insensitive behaviour of ubiquitous computing devices.

Discovering services in the local broadcast domain is easy from the application point of view. However, from the network point of view, especially when wireless networks are also involved, it is wasteful, as query and response are broadcast on all access points at the lowest data rate, ignoring efficient transmission modes. It also does not scale beyond the single broadcast domain, as this would require deployment of IP multicast, which has yet to happen despite decades of trying. We introduce Stateless DNS as an efficient and broader range alternative. Stateless DNS requires no action from the network service provider, improves upon privacy and comes with incremental deployment options. While providing a well-known DNS interface to the applications, it can identify organizational boundaries and uses existing DNS caches for performance.

By tweaking the BGP configurations, the network operators are able to express their interdomain routing preferences, designed to accommodate a myriad goals. Given the complex interactions between policies in the Internet, the origin AS by itself cannot ensure that only by configuring a routing policy it can also achieve the anticipated results. Moreover, the definition of routing policies is a complicated process, involving a number of subtle tuning operations prone to errors. In this paper, we propose the BGP Visibility Scanner which allows network operators to validate the correct implementation of their routing policies, by corroborating the BGP routing information from approximately 130 independent observation points in the Internet. We exemplify the use of the proposed methodology and also perform an initial validation for the BGP Visibility Scanner capabilities through various real operational use cases.

Airbnb.com is an online community marketplace that facilitates short-term rentals of "unique spaces" around the world. Since its launch, Airbnb has grown from a few hundred bookings in 2008 to over ten million nights of cumulative bookings worldwide by the end of 2012, spanning more than 300,000 properties in 192 countries. Our work investigates the consequences of the rise of Airbnb as seen by the local economy, focusing on quantifying the impact of Airbnb's growth on the local hotel industry. To explore this question, we consider the state of Texas, where Airbnb adoption exhibits significant spatio-temporal variation across a large number of city-level markets. We leverage a dataset we collected from Airbnb.com,  comprehensively spanning the thousands of Texas properties listed on Airbnb from 2008 to 2013, which we combine with a panel of quarterly tax revenue data for all hotels in the state of Texas from 2001 to 2013. Our analysis provides evidence that the hotel industry has experienced a decrease in revenue due to the entry of Airbnb in the market. Specifically, we find that a 1% increase in the size of the Airbnb market results in a 0.05% decrease in hotel revenue. Furthermore, our results indicate that losses are unevenly distributed among hotels in different price segments, with lower-priced hotels experiencing the largest impact. 

Intercell coordination and cooperation techniques are some of the most promising approaches to increase the spectral efficiency of future wireless systems as required by
the forecasted market needs. Among them, intercell coordinated scheduling (ICCS) arises as a near-term feasible solution due to its lower inter-BS communication requirements when compared to full cooperative approaches. In this paper we present our proposed Reservation Information Aware Intercell Coordinated Scheduling (RIA-ICCS) solution which considers application reservation information when constructing an interference graph for ICCS purposes.

In this talk, we discuss a theoretical framework to evaluate the throughput of underwater networks over an ensemble of node topologies and propagation environments. We start with a review of the properties of underwater acoustic communications.

Suppose that we have a network of n processors where each processor knows its own ID and the IDs of its neighbors. Processors communicate in synchronous rounds by writing messages on a whiteboard, which is visible to all of them. The goal is to design a protocol at the end of which every processor knows the topology of the network.

Motivated by limitations in today's host-centric IP network, several recent "clean-slate" network architectures have proposed alternate first-class principals, such as content, services, or users.

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.