Abstract
Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

Abstract
Erasure codes have been employed in a wide range of applications to increase content availability, improve channel reliability, or to reduce downloading time. For several applications, such as P2P file sharing, MDS erasure codes are more suitable as the network is typically the most constrained resource, not the CPU. Rateless MDS erasure codes also enable to adjust encoding and decoding algorithms as function of dynamic variables to maximize erasure coding gains. State-of-the-art MDS erasure codes are either fixed-rate or have practical limitations. We propose Storm erasure codes, a rateless MDS construction of Reed-Solomon codes over the finite field F-p2, where p is a Mersenne prime. To the best of our knowledge, we are the first to propose a rateless construction (n can be increased in steps of k) with Theta (n log k) encoding time complexity and min {Theta(n log n), Theta(k log(2) k)} upper bound for decoding time complexity. We provide the complexity analysis of encoding and decoding algorithms and evaluate Storm's performance.

Abstract
ns-3 is the successor of ns-2, the most popular network simulator. Network simulators such as ns-3 play an important role on understanding, designing, and building Internet systems. But simulations are only as good as their models, and the simulation of large scale Internet systems using accurate and complex models is a challenging task. ns-3 simulates realistically the network stack but the scale and complexity of the Internet topology is, from our point of view, limited by the IP forwarding operations. This work proposes CIDRarchy, an IPv4 routing protocol for ns-3 that uses CIDR as the base to create an hierarchical Internet-like network topology that enables (1) IP forwarding with constant time complexity and automatic IPv4 address assignment, and (2) the implementation of an ns-3 helper to ease network topology creation. We implemented CIDRarchy, evaluated its performance, and obtained simulation time reduction over existing ns-3 routing protocols implementations that can reach over one order of magnitude. Copyright © 2015 ICST.

Abstract
The increasing number of television channels, on-demand services and online content, is expected to contribute to a better quality of experience for a costumer of such a service. However, the lack of efficient methods for finding the right content, adapted to personal interests, may lead to a progressive loss of clients. In such a scenario, recommendation systems are seen as a tool that can fill this gap and contribute to the loyalty of users. Multimedia content, namely films and television programmes are usually described using a set of metadata elements that include the title, a genre, the date of production, and the list of directors and actors. This paper provides a deep study on how the use of different metadata elements can contribute to increase the quality of the recommendations suggested. The analysis is conducted using Netflix and Movielens datasets and aspects such as the granularity of the descriptions, the accuracy metric used and the sparsity of the data are taken into account. Comparisons with collaborative approaches are also presented.

Abstract
This short paper presents a game for collecting metadata to describe video content. Tags, introduced by registered players on a given timecode of the video, are collected and validated based on a collaborative scoring mechanism that excludes erratic annotations. The system follows a gamification approach for motivating users and includes processes for semantically relating concepts.

Abstract