In wireless sensor networks, the quality of the provided data is influenced by the properties of the sensor nodes. Often deployed in large numbers, they usually consist of low-cost components where failures are the norm, even more so in harsh outdoor environments. Current fault detection techniques, however, consider the sensor data alone and neglect vital information from the nodes’ hard- and software. As a consequence, they can not distinguish between rare data anomalies caused by proper events in the sensed data on one side and fault-induced data distortion on the other side. In this paper, we contribute with a novel, open-source sensor node platform for monitoring applications such as environmental monitoring. For long battery life, it comprises mainly low-power components. In contrast to other sensor nodes, our platform provides self-diagnostic measures to enable active node-level reliability. The entire sensor node platform including the hardware and software components has been implemented and is publicly available and free to use for everyone. Based on an extensive and long-running practical experiment setup, we show that the detectability of node faults is improved and the distinction between rare but proper events and fault-induced data distortion is indeed possible. We also show that these measures have a negligible overhead on the node’s energy efficiency and hardware costs. This improves the overall reliability of wireless sensor networks with both, long battery life and high-quality data.

The use of fault detection and tolerance measures in wireless sensor networks is inevitable to ensure the reliability of the data sources. In this context, immune-inspired concepts offer suitable characteristics for developing lightweight fault detection systems, and previous works have shown promising results. In this article, we provide a literature review of immune-inspired fault detection approaches in sensor networks proposed in the last two decades. We discuss the unique properties of the human immune system and how the found approaches exploit them. With the information from the literature review extended with the findings of our previous works, we discuss the limitations of current approaches and consequent future research directions. We have found that immune-inspired techniques are well suited for lightweight fault detection, but there are still open questions concerning the effective and efficient use of those in sensor networks.

With increasing complexity, shrinking feature sizes, and lower voltages new challenges arise for the verification of modern system on chip devices, e.g., due to effects caused by the interplay of digital and analog peripherals. Many of the undesired effects are only observable in realistic applications. In order to re-enact the incorrect behavior of the SoC under lab conditions additional equipment (e.g., power supplies, pattern generators) is required. Additionally, test parameters need to be transferred to the design under test (DUT) and test results gathered on the device have to be sent back for inspection.Due to the real-time constraints of the user application on the DUT the host can not simply control the DUT 'as is'. In this paper we dissect various synchronization and communication options commonly available on SoC and evaluate their usefulness for post-silicon testing. A generic solution is presented that provides an abstract API supporting various kinds of interfaces to achieve synchronization and communication, thus enabling convenient adaption to different test setups depending on the available resources.