Abstract
Visual data monitoring in wireless sensor networks can significantly enrich a large set of surveillance and general purpose monitoring applications. However, transmission of image snapshots or video streams can rapidly deplete the energy resources of the deployed nodes, turning energy efficiency into a major optimization issue. During wireless transmissions, packets can be corrupted directly affecting the monitoring quality of the applications. One reasonable way to reduce quality loss is the transmission of redundant packets for higher error resilience, but additional packet transmissions may incur in undesirable energy consumption. Frequently, some monitoring quality loss may be tolerated since visual information retrieved from source nodes may have different relevance for the applications, according to the monitoring requirements and the current sensors' poses and fields of view. In such way, we propose that only high-relevant source nodes will transmit redundant packets, assuring error resilience only for the most relevant visual data for the monitoring application. Doing so, energy is saved over the network when fewer packets are transmitted in average, potentially enlarging the network lifetime with reduced impact to the overall monitoring quality. © 2013. WSEAS Transactions on Communications.

Abstract
During the last few years, the demand for Real-Time (RT) communication has been steadily increasing due to a wide range of new applications. Remarkable examples are VoIP (Voice over IP) and Networked Control Systems (NCS). For such RT applications, the support of timely communication services is one of the major requirements. The purpose of this chapter is to survey the state-of-the-art on RT communication in CSMA-based networks and to identify the most suitable approaches to deal with the requirements imposed by next generation communication systems. This chapter focuses on one of the most relevant solutions that operate in shared broadcast environments, according to the CSMA medium access protocol, the IEEE 802.11 standard. From this survey, it becomes clear that traditional CSMA-based networks are not able to deal with the requirements imposed by next generation communication systems. More specifically, they are not able to handle uncontrolled traffic sources sharing the same broadcast environment. © 2013, IGI Global.

Abstract
The IEEE 802.15.4/ZigBee set of standards is one of the most used wireless sensor network technologies. This set of standards supports cluster-tree networks, which are suitable topologies for wide-scale deployments. The design of wide-scale wireless sensor networks is a challenging task because it is difficult to test, analyse and validate new designs in real scenarios. Thus, simulation becomes a convenient and feasible method for its assessment before deployment. Within this context, we provide a set of simulation models for IEEE 802.15.4/ZigBee-based networks, which are able to deal with wide-scale cluster-tree wireless sensor networks and to address their major challenges. The provided simulation models implement important mechanisms for the assessment of wide-scale cluster-tree networks and associated data communication mechanisms, enabling an easier design and test of wide-scale wireless sensor network implementations.

Abstract
The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries in WSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.

Abstract
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.

Abstract
Energy consumption is a major concern in Wireless Sensor Networks (WSNs) since nodes are powered by batteries. Usually, batteries have low capacity and can not be replaced due to economic and/or logistical issues. In addition, batteries are complex devices as they depend on electrochemical reactions to generate energy. As a result, batteries exhibit non-linear behaviour over time, which makes difficult to estimate their lifetime. Analytical battery models are abstractions that allow estimating the battery lifetime through mathematical equations, taking into account important effects such as rate capacity and charge recovery. The recovery effect is very important since it enables charge gains in the battery after its electrochemical stabilization. Sleep scheduling approaches may take advantage of the recovery effect by adding sleep periods in the node activities in order to extend the network lifetime. This work aims to analyse the recovery effect within WSN context, particularly regarding low-power nodes. To do so, we use an analytical battery model for analysing the battery performance over time, during the node execution. © Springer International Publishing AG 2017.