In the context of Opportunistic Networking (OppNet), designing routing and delivery protocols is currently an open and active line of research. In some OppNet scenarios, destination addresses are not always known by sending applications. Profile-cast models solve this problem by allowing message destinations to be users or groups of users defined by their profiles. These profiles provide very effective ways of characterizing nodes in terms of node's attributes such as their profession, interests or typical whereabouts, for example. However, there are strong limitations in OppNet Profile-casting. There is no current way of representing special profiles defined by relative delivery functions such as best, maximum or over-the-average: nodes belong to these relative profiles taking into account not only attributes from the very same node but also relative to others from the same profile. In this article, we introduce Relcast, a Profile-cast model that allows messages to be sent to profiles defined in terms of relative delivery functions. Additionally, we present Explore and Wait, a composite routing-delivery scheme that uses optimal stopping theory-based delivery strategies to route Relcast messages. We show, using simulations that this routing-delivery scheme performs better than traditional approaches that use state-of-the-art routing-delivery primitives.
The students' lack of motivation is a usual problem. The students value more the obtention of the degree than the developing of competences and skills. In order to fight this, we developed a gamification's experience based on merits and leaderboards. The merits are linked to the attainment of skills and competences that students usually do not appreciate. During the year 2016, we are carrying out a pilot involving 950 students at the Graduate of Engineering in Computer Science at the Autonomous University of Barcelona (UAB).
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