Some of the most difficult problems to deal with when using Wireless Sensor Networks (WSNs) are related to the unreliable nature of communication channels. In this context, the use of cooperative diversity techniques and the application of network coding concepts may be promising solutions to improve the communication reliability. In this paper, we propose the NetCoDer scheme to address this problem. Its design is based on merging cooperative diversity techniques and network coding concepts. We evaluate the effectiveness of the NetCoDer scheme through both an experimental setup with real WSN nodes and a simulation assessment, comparing NetCoDer performance against state-of-the-art TDMA-based (Time Division Multiple Access) retransmission techniques: BlockACK, Master/Slave and Redundant TDMA. The obtained results highlight that the proposed NetCoDer scheme clearly improves the network performance when compared with other retransmission techniques.

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks.

The use of mobile nodes to collect data in a Wireless Sensor Network (WSN) has gained special attention over the last years. Some researchers explore the use of Unmanned Aerial Vehicles (UAVs) as mobile node for such data-collection purposes. Analyzing these works, it is apparent that mobile nodes used in such scenarios are typically equipped with at least two different radio interfaces. The present work presents a Dual-Stack Single-Radio Communication Architecture (DSSRCA), which allows a UAV to communicate in a bidirectional manner with a WSN and a Sink node. The proposed architecture was specifically designed to support different network QoS requirements, such as best-effort and more reliable communications, attending both UAV-to-WSN and UAV-to-Sink communications needs. DSSRCA was implemented and tested on a real UAV, as detailed in this paper. This paper also includes a simulation analysis that addresses bandwidth consumption in an environmental monitoring application scenario. It includes an analysis of the data gathering rate that can be achieved considering different UAV flight speeds. Obtained results show the viability of using a single radio transmitter for collecting data from the WSN and forwarding such data to the Sink node.

The use of cooperative diversity techniques and network coding concepts are promising solutions to improve the communication reliability in industrial Wireless Sensor Networks (WSNs). In this paper, we propose the NetCoDer scheme to address this problem, whose design is based in these concepts. The effectiveness of the NetCoDer scheme is evaluated through both an experimental setup with real WSN nodes and a simulation assessment, comparing its performance against stateof-the-art TDMA-based retransmission techniques.

The increasing adoption of the Internet of things and cloud computing in recent years provided the increasing development and improvement of various well-known approaches, such as the ambient assisted living approach. The merging of Internet of things and cloud brought about the so-called CloudIoT paradigm. CloudIoT intends to extend both technologies to make possible developing the next generation of smart environments, such as healthcare applications. New healthcare applications demand an increasing capacity of resources for storing, processing, and transmitting data. Looking at this scenario, along with the growing number of devices connected to the Internet of things, we must consider providing mechanisms to mitigate the excessive data offloading on the network, the latency between nodes, and even the unnecessary waste of computing power. In this article, we present an efficient and effective CloudIoT-based healthcare architecture for ambient assisted living environments. The innovation of our approach lies on the use of a game theory approach (by means of a stochastic search algorithm) to improve efficiency and latency of the CloudIoT network. This proposal aims to provide better availability levels to the whole environment. Experiments performed through simulation have shown us a remarkable improvement of network parameters, by applying a stochastic search algorithm called Gur game, when compared to a baseline application.

In some Wireless Sensor Network applications the sensor nodes share the same sensing activity, which means that for a considerable number of applications, not all nodes are required to perform sensing tasks during the network lifetime. Sleep-scheduling approaches can be applied in this scenario, enabling that some nodes turn off their radios, saving energy and bandwidth, as long as there are enough nodes to ensure the required Quality of Service (QoS) of the network. This paper presents a new adaptive approach for QoS and energy management in IEEE 802.15.4 networks, entitled Skip Game. This approach targets a trade-off between increasing the network lifetime and maintaining the QoS of the network, aiming a greater number of nodes to participate in the monitoring application. In order to evaluate the proposed approach, we performed some experiments using the OMNeT++ simulator tool under the MiXiM framework. The results show that the Skip Game outperforms both the traditional Gur Game and Gureen Game approaches in terms of QoS provision and network lifetime.

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