Abstract
Wireless Underground Networks (WUNs) include communications links between buried nodes and between buried and aboveground nodes. WUNs have many applications, such as border surveillance, agriculture monitoring, and infrastructure monitoring. Recent studies have shown that they are feasible and have deployment advantages over wired networks. Yet, so far WUNs evaluations have been done using testbeds only, and a tool enabling simulations on TCP/IP WUNs is lacking. We propose a simulator of TCP/IP wireless underground networks based on ns-3. The simulator was validated against experimental results for 433 MHz and 2.4 GHz frequency bands. The results show its accuracy for most of the communications scenarios. © 2014 IEEE.

Abstract
Available wireless sensor networks targeting the domain of healthcare enables the development of new applications and services in the context of E-Health. Such networks play an important role in several scenarios of patient monitoring, particularly those where data collection is vital for diagnosis and/or research purposes. However, despite emerging solutions, wearable sensors still depend on users' acceptance. One proposed solution to improve wearability relies on the use of smaller sensing nodes, requiring more energy-efficient networks, due to smaller room available for energy sources. In such context, smaller wireless sensor network nodes are required to work long time periods without human intervention and, at the same time, to provide appropriate levels of reliability and quality of service. Satisfaction of these two goals depends on several key factors, such as the routing protocol, the network topology, and energy efficiency. This paper offers a solution to increase the network lifetime based on a new Energy-Aware Objective Function used to design a Routing Protocol for Low-Power and Lossy Networks. The proposed Objective Function uses the Expected Transmission Count Metric and the Remaining Energy on each sensor node to compute the best paths to route data packets across the network. When compared with state of the art solutions, the proposed method increases the network lifetime by 21% and reduces the peaks of energy consumption by 12%. In this way, wireless sensor network nodes wearability can be improved, making them smaller and lighter, while maintaining the required performance.

Abstract
IEEE 802.11-based wireless multimedia sensor networks (WMSN) are a cost-effective and flexible solution for video monitoring scenarios. Yet, they suffer from three major problems: bad performance, throughput unfairness, and energy inefficiency. Several approaches have been considered to tackle these problems but they are too restrictive or complex. In this paper we propose a scheduling approach using FM as a control channel to address the energy inefficiency problem. By taking advantage of the FM radio characteristics - higher coverage and lower energy consumption than Wi-Fi, our proposed approach uses FM as an always-on point-to-multipoint control channel used to turn off the nodes' Wi-Fi radio interfaces when they are not needed to transmit, receive, or relay data. Numerical and simulation analysis shows that our proposed scheduling mechanism significantly reduces energy consumption, while preserving performance and fairness characteristics.

Abstract
The usage of Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), and sensors in surveillance, maintenance and inspection of underwater facilities is increasing the need for broadband, cost-e ective communications solutions. Current solutions, mainly based on acoustic communications, enable long ranges but provide low bitrates and have high communication delays. Despite its strong attenuation underwater, RF is envisioned as a technology to enable broadband, short-range communications. We present an ns-3 and an experimental evaluation of IEEE 802.11 networks in freshwater at 700 MHz, 2.4 GHz and 5 GHz frequency bands. Evaluation results con rm the accuracy of the new developed ns-3 underwater RF propagation model and show that IEEE 802.11 networks are feasible for broadband, short range underwater communications, with range and throughput exceeding 2 m and 100 Mbit/s, respectively.

Abstract
Wireless Sensor Networks (WSNs) are made of a large amount of small devices that are able to sense changes in the environment, and communicate these changes throughout the network. An example of such network is a photo voltaic (PV) power plant, where there is a sensor connected to each solar panel. Because such a network covers a large area, the number of sensors can be very large. The task of each sensor is to sense the output of the panel which is then sent to a central node for processing. As the network grows, it becomes impractical and even impossible to configure all these nodes manually. And so, the use of self-organization and auto-configuration algorithms becomes essential. In this paper, two algorithms are proposed that can be used to allow each node in the network to automatically identify its closest neighbors as well as its relative location in the network using the value of the Received Signal Strength indicator (RSSI) of the messages sent back and forth during the setup phase. Results show that the error in neighbor identification decreases as we increase the number of RSSI values used for decision making. Additionally, the number of nodes in the network affects the setup error greatly. However, the value of the error is still acceptable even for high number of simulated columns.

Abstract
Real-time monitoring applications deployed in Low-power and Lossy Networks may generate flows sensitive to delay, where the information is useful for the destination only if it is received within a strict delay boundary. Data packets that will likely miss the application deadline could be discarded during their routing through the network or even be not transmitted at all, thus contributing for a better usage of the network resources. This paper presents RA-EEDEM, a set of modifications made to RPL that improve the End-to-End Delay (EED) estimation accuracy. The RA-EEDEM modifications include changes to the RPL metrics and to its Objective Function (OF). The results show that RA-EEDEM improves the accuracy of EED estimation while minimizing its impact on the average EED and Packet Reception Ratio (PRR).