Abstract
The rise of the Internet of Things and the growth of the IP cameras market are making Wireless Video Sensor Networks (WVSNs) popular. In turn, Wi-Fi is becoming the enabling technology for WVSNs due to its flexibility, high bitrates provided and low cost; however, these networks suffer from three major problems: bad performance, throughput unfairness, and energy inefficiency. In order to address the lack of holistic solutions to solve these problems, we propose the FM-WiFIX+ solution. This solution uses FM radio as an out-of-band control channel to signal when a video sensor should turn its IEEE 802.11 interface OFF, thus saving energy. The results obtained with a proof-of-concept prototype show that for a network with 7 nodes the proposed solution can achieve gains of energy up to 48 %, while maintaining good levels of performance and throughput fairness.

Abstract
The demand for broadband underwater communications is being pushed by the increasing use of Autonomous Underwater Vehicles (AUV) in underwater missions. IEEE 802.11, already used in AUV for above water communications, can also be employed underwater to enable cost-effective, high bandwidth, short range communications. However, the high RF attenuation underwater induces high variations of received power, which may affect the performance of existing rate adaptation algorithms designed for over-the-air networks. This paper evaluates the most relevant state-of-the-art IEEE 802.11 rate adaptation algorithms in underwater environment. Simulation results show the AARF algorithm outperforms the widely used Minstrel algorithm, as well as the CARA, RRAA and ONOE algorithms. Copyright 2015 ACM.

Abstract
Peer-to-Peer networks are extensively used for largescale file sharing. As more information flows through these networks, people are becoming increasingly concerned about their privacy. Traditional P2P file sharing systems provide performance and scalability at the cost of requiring peers to publicly advertise what they download. Several P2P privacyenhancing systems have been proposed but they still require peers to advertise, either fully or partially, what they download. Lacking alternatives, users have adopted anonymity systems for P2P file sharing, misunderstanding the privacy guarantees provided by such systems, in particular when relaying traffic of insecure applications such as BitTorrent. Our goal is to prevent any malicious peer(s) from ascertaining users' content interests so that plausible deniability always applies. We propose a novel P2P file sharing model, Mistrustful P2P, that (1) supports file sharing over open and untrustworthy P2P networks, (2) requires no trust between users by avoiding the advertisement of what peers download or miss, and (3) still ensures deterministic protection of user's interests against attacks of size up to a configured privacy protection level. We hope that our model can pave the ground for a new generation of privacyenhancing systems that take advantage of the new possibilities it introduces. We validate Mistrustful P2P through simulation, and demonstrate its feasibility.

Abstract
Wireless Underground Networks (WUNs) have applications such as agriculture, border surveillance, maintenance of playing fields, and infrastructure monitoring. When designing a sensor network for one of these applications some of the sensors (communication nodes) will be buried underground, which means the propagation medium will be the soil or hybrid (air plus soil) in case of one of the nodes is aboveground. Thus, new models have to be implemented in existing simulators, in order to enable the proper simulation of these communications scenarios. This paper presents a new model, named underground model, and discusses its integration into the NS-3 simulator. The underground model enables the simulation of WUNs, including network topologies with underground and aboveground nodes. The accuracy of the underground model is shown for two frequency bands by comparing simulations results with experimental results. © 2015 ACM.

Abstract
In IEEE 802.11 based wireless networks adding more access points does not always guarantee an increase of network capacity. In some cases, additional access points may contribute to degrade the aggregated network throughput as more interference is introduced. This paper characterizes the power interference in CSMA/CA based networks consisting of nodes using directional antenna. The severity of the interference is quantized via an improved form of the Attacking Case metric as the original form of this metric was developed for nodes using omnidirectional antenna. The proposed metric is attractive because it considers nodes using directional or omnidirectional antenna, and it enables the quantization of interference in wireless networks using multiple transmission power schemes. The improved Attacking Case metric is useful to study the aggregated throughput of IEEE 802.11 based networks; reducing Attacking Case probably results in an increase of aggregated throughput. This reduction can be implemented using strategies such as directional antenna, transmit power control, or both.

Abstract
Wireless Sensor Networks (WSNs) can be deployed using available hardware and software. The Contiki is an operative system compatible with a wide range of WSN hardware. A Contiki development environment named InstantContiki is also available and includes the Cooja simulator, useful to test WSN simulation scenarios prior to their deployment. Cooja can provide realistic results since it uses the full Contiki's source code and some motes can be emulated at the hardware level. However this implies extending the simulation runtime, which is heightened since the Cooja is single threaded, i.e, it makes use of a single core per instant of time, not taking advantage of the current multi-core processors. This chapter presents a framework to automate the configuration and execution of Cooja simulations. When a multi-core processor is available, this framework runs multiple simultaneous Cooja instances to reduce simulations runtime in exchange of higher CPU load and RAM usage.