Abstract
In the last decade, the FlexRay communication protocol has been promoted as a standard for dependable in-vehicular communications. In the FlexRay protocol, the communication timeline is organized as a sequence of four segments, whereas the Static Segment assigns a set of static slots for the transmission of synchronous messages. In this paper, we address the following problems: "How to efficiently transmit periodic messages in the Static Segment without requiring their periods to be multiples of, or to be synchronized with the FlexRay Communication Cycle?" "Is it possible to guarantee that periodic messages are transferred before their deadlines, without imposing such strict synchronization?" Unlike traditional approaches that use linear-programming based techniques, we evaluate the minimum number of allocated slots using traditional Response Time Analysis (RTA). The use of RTA techniques allows us to consider the timing requirements associated to each of the asynchronous message streams. Unlike other approaches, the RTA-based technique proposed in this paper: (a) is able to deal with message stream sets where periods are not multiple of the FlexRay cycle duration and (b) does not require the strict synchronization between tasks/signals at the application layer and slots at the FlexRay communication controller. The proposed slot allocation scheme may be of high practical interest when considering the interconnection of FlexRay/CAN in-vehicular communication systems, allowing the remapping of existing CAN message streams to FlexRay.

Abstract
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.

Abstract
Scalability and topological stability are two of the most challenging issues in current wireless mesh networks (WMNs) deployments. In the literature, both the scalability and the topological stability of WMNs are described as likely to suffer from poor performance due to the ad hoc nature of the underlying IEEE 802.11 mechanisms. The main contribution of this article is a comprehensive review of the main topological stability and scalability-related issues in IEEE 802.11s-based networks. Moreover, the most relevant proposed solutions are surveyed, where both the drawbacks and the merits of each proposal are highlighted. At the end of the article, some open research challenges are presented and discussed. It is expected that this work may serve as motivation for more and deeper research on these issues to allow the design of future more stable and scalable IEEE 802.11s mesh networks deployments. Copyright (c) 2015 John Wiley & Sons, Ltd.

Abstract
The use of wireless sensor network nodes to support reliable communication exposes some challenging issues. For instance, the reduced available bandwidth combined with an error-prone communication medium impairs the provision of reliable communication services. Network coding techniques can be useful to mitigate some of these issues, where multiple message groups can be combined into single messages and retransmitted to their destinations, improving the network reliability and reducing the bandwidth consumption. However, an effective use of network coding requires the availability of wireless sensor network nodes able to encode/decode messages within the required timing constraints. This paper reports an experimental assessment of commercial off-the-shelf wireless sensor network nodes, running a set of network coding encoding/decoding tasks. The assessed nodes range from the high-performance ARM Cortex-M7 to the low capability Arduino Uno platforms, including some of the most popular ARM Cortex and ATMEL AVR processors. The performed experimental assessment demonstrates that highly complex network coding techniques (with fields as large as F28) can be efficiently implemented on a wide range of wireless sensor network nodes, including ARM Cortex, ATMEL AVR, and Arduino Uno platforms, smoothing some relevant reliable communication implementation issues.

Abstract
The complexity of electronic systems embedded in modern vehicles has led to the adoption of distributed implementations where different communication protocols are used. Although literature addressing vehicular networks presents several methods for the timing analysis of automotive systems, there is not a reference model for the holistic time analysis of heterogeneous systems where FlexRay/CAN protocols are used. In this work we propose a reference model for timing and schedulability analysis of heterogeneous FlexRay/CAN networks. The proposed reference model can be used to compute end-to-end response times and to analyze local components, such as response times in a specific network segment.

Abstract
In wireless visual sensor networks comprised of multiple camera-enabled sensors, source prioritization can be exploited to soften the impact of congestion, packet loss and energy depletion when higher relevant packets are processed. However, for such optimizations, source nodes have to be properly prioritized according to some effective metric. When performing visual sensing over moving targets, sensors may view different parts of the targets, which may have particular relevance for monitoring applications. In this context, this paper proposes a low-cost mathematical approach that associates a priority level to each visual source node according to the viewed segments of the targets' perimeter, and such priority may then be exploited for a large set of optimizations. A complete mathematical formulation and numerical results are presented to base the proposed approach.