Abstract
The use of wireless sensor networks (WSN) to support critical monitoring applications is becoming a relevant topic of interest. These networks allow a highly flexible approach to data monitoring and, consequently, a major breakthrough for several application domains, from industrial control applications to large building domotics and health care applications. One of the major impairments of using wireless networks to support critical monitoring applications is the electromagnetic noise, which may increase the packet loss ratio to unacceptable values. In this paper, we assess different techniques of cooperative communication and network coding that can be useful to mitigate the aforementioned problem. These techniques may be implemented in WSN nodes in conformance with the IEEE 802.15.4 standard, to reduce the impact of electromagnetic interferences upon the packet loss ratio. In this paper, we report an experimental assessment of the network coding and cooperative diversity techniques, where the network is subjected to a controlled electromagnetic interference inside of an anechoic chamber. The experimental results show that, by using these techniques, it is possible to increase the success rate of communication in typical electromagnetic noisy environments.

Abstract
Wireless sensor networks (WSNs) can be used to support monitoring activities in a wide range of applications and communication environments. Its usage in extreme conditions, in what concerns pressure, temperature, and humidity, must be carefully assessed before the network deployment. In particular, the temperature variations have a direct impact upon the behavior of WSNs through the batteries of sensor nodes. These electrochemical devices are highly susceptible to temperature variations, which modifies the offered effective charge capacity. In this context, it is difficult to estimate the behavior of batteries over time, impairing the extraction of relevant information for energy-aware approaches. Such information, particularly battery state of charge, voltage, and lifetime, is often used by WSN simulators to predict the communication behavior in different scenarios. Nevertheless, WSN simulators generally use simplistic battery models, causing significant deviations in simulation results when compared with actualWSN deployments. This paper describes the implementation of the Temperature-Dependent Kinetic Battery Model (T-KiBaM) in the Castalia simulator, which enables a considerable improvement of the accuracy of simulations in communication environments with different temperature conditions. An experimental assessment has been performed with temperature variations over time to validate the usage of the T-KiBaM battery model. The experimental results indicate that the T-KiBaM model is quite accurate when estimating battery behavior under both different temperature set points and different temperature variations.

Abstract
Wireless sensor networks have been considered as an effective solution to a wide range of applications due to their prominent characteristics concerning information retrieving and distributed processing. When visual information can be also retrieved by sensor nodes, applications acquire a more comprehensive perception of monitored environments, fostering the creation of wireless visual sensor networks. As such networks are being more often considered for critical monitoring and control applications, usually related to catastrophic situation prevention, security enhancement and crises management, fault tolerance becomes a major expected service for visual sensor networks. A way to address this issue is to evaluate the system dependability through quantitative attributes (e.g., reliability and availability), which require a proper modeling strategy to describe the system behavior. That way, in this paper, we propose a methodology to model and evaluate the dependability of wireless visual sensor networks using Fault Tree Analysis and Markov Chains. The proposed modeling strategy considers hardware, battery, link and coverage failures, besides considering routing protocols on the network communication behavior. The methodology is automated by a framework developed and integrated with the SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) tool. The achieved results show that this methodology is useful to compare different network implementations and the corresponding dependability, enabling the uncovering of potentially weak points in the network behavior.

Abstract
Wireless Sensor Networks (WSN) are enabler technologies for the implementation of the Internet of Things (IoT) concept. WSNs provide an adequate infrastructure for the last-link communication with smart objects. Nevertheless, the wireless communication medium being inherently unreliable, there is the need to increase its communication reliability. Techniques based on the use of cooperative communication concepts are one of the ways to achieve this target. Within cooperative communication techniques, nodes selected as relays transmit not only their own data, but also cooperate by retransmitting data from other nodes. A fundamental step to improve the communication reliability of WSNs is related to the use of efficient relay selection techniques. This paper proposes a relay selection technique based on multiple criteria to select the smallest number of relay nodes and, at the same time, to ensure an adequate operation of the network. Additionally, two relay updating schemes are also investigated, defining periodic and adaptive updating policies. The simulation results show that both proposed schemes, named Periodic Relay Selection and Adaptive Relay Selection, significantly improve the communication reliability of the network, when compared to other state-of-the-art relay selection schemes.

Abstract

Abstract
Topology formation in wireless sensor networks is usually done assuming just either the geographical proximity between nodes or the signal strength of communication. In this paper, a heuristic called DbCTF is proposed to guide the formation of cluster-tree networks, which also considers data clustering techniques. The use of DbCTF allows the setup of a data-based topology in the cluster-tree, and also the prioritisation of monitored regions in which relevant events may be occurring. The performance of DbCTF has been compared with a state-of-the-art algorithm, for the specific case of a classical WSN laboratory experiment. The simulation assessment revealed that the cluster-tree formed by DbCTF was able to reduce by more than 20% the average communication delay of message streams conveying critical data, and was also able to increase by more than 35% the average lifetime of the network.