Abstract
WSN can be deployed using widely available hardware and software solutions. The Contiki is an open source operative system compatible with a wide range of WSN hardware. A Contiki development environment named InstantContiki is also available and includes the Cooja simulation tool, useful for the simulation of WSN scenarios, prior to their deployment. This simulation tool can provide realistic results since it uses the full Contiki's source code and some motes can be emulated at the hardware level. However, the Cooja simulator uses one process per simulation, not taking advantage of multiple core processors. In this paper we propose a framework to automate the execution of simulations of multiple scenarios and configurations in Cooja. When a multiple cores processor is available, this framework can run multiple simultaneous Cooja instances, taking advantage of processing resources and contributing to reduce the total simulation runtime.

Abstract
A common problem in networking research and development is the duplicate effort of writing simulation and implementation code. This duplication can be avoided through the use of fast-prototyping methodologies, which enable reusing simulation code in real prototyping and in production environments. Although this functionality is already available by using ns-3 emulation, there are still limitations regarding the support of real network interfaces and easy configuration of the network settings, such as IP and MAC addresses. In this paper we propose an improved version of the ns-3 emulation component by introducing new functionalities that address these limitations. The new functionalities include the support of new types of real network interfaces and the easier integration of emulation nodes with existing networks by means of a new auto-configuration mechanism for ns-3 nodes. Experimental results obtained in a laboratorial testbed and in a real vehicular network testbed demonstrate the new functionalities proper operation, and their backwards compatibility with previously coded ns-3 scenarios. Copyright © 2015 ICST.

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.