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).

Abstract
Biomedical wireless sensor networks are a key technology to support the development of new applications and services targeting patient monitoring, in particular, regarding data collection for medical diagnosis and continuous health assessment. However, due to the critical nature of medical applications, such networks have to satisfy demanding quality of service requirements, while guaranteeing high levels of confidence and reliability. Such goals are influenced by several factors, where the network topology, the limited throughput, and the characteristics and dynamics of the surrounding environment are of major importance. Harsh environments, as hospital facilities, can compromise the radio frequency communications and, consequently, the network's ability to provide the quality of service required by medical applications. Furthermore, the impact of such environments on the network's performance is hard to manage due to its random and unpredictable nature. Consequently, network planning and management, in general or step-down hospital units, is a very hard task. In such context, this work presents a quality of service based management tool to help healthcare professionals supervising the network's performance and to assist them managing the admission of new sensor nodes (i.e., patients to be monitored) to the biomedical wireless sensor network. The proposed solution proves to be a valuable tool both, to detect and classify potential harmful variations in the quality of service provided by the network, avoiding its degradation to levels where the biomedical signs would be useless; and to manage the admission of new patients to the network.

Abstract
The deployment of thousands of tiny devices inter-networked together and accessible through the Internet is the result of the increasing trend towards enabling the concepts of Internet-of-Things. As these devices may be scattered in a unplanned way, a routing protocol is needed. The RPL protocol is the IETF proposed standard protocol for IPv6-based multi-hop Wireless Sensor Networks (WSN). RPL requires that communication paths go through a central router which may provide suboptimal paths, making no distinction of the applications the nodes run. To address these issues, an Application-Driven extension to RPL is proposed which enables the increase of the WSN lifetime by limiting the routing and forwarding functions of the network mainly to nodes running the same application. This paper evaluates the proposed solution coded in ContikiOS by means of Cooja simulations, and compares it against regular RPL. Simulation results confirm that the proposed solution provides lower energy consumption, lower end-to-end delays, and lower total number of packets transmitted and received.

Abstract
Stub Wireless Mesh Networks (WMNs) are used to extend Internet access. The use of multiple channels improves the capacity of WMN but significant challenges arise when nodes are limited to a single-radio interface to form the WMN. In particular, the assignment of mesh nodes to channels results on the creation of multiple sub-networks, one per channel, where individual capacity may depend on the sub-network topologies This paper identifies the relevant topological characteristics of the sub-networks resultant from the channel assignment process and studies, through simulation, the impact and relative importance of those characteristics on the maximal throughput enabled by the stub WMN. The number of nodes in the gateways neighborhood and the hidden node problem in the gateways neighborhood were identified as the characteristics having the highest impact on the WMN throughput.