An Open-Source Wireless Sensor Node Platform with Active Node-Level Reliability for Monitoring Applications

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.

Single-seed cascades on clustered networks

We consider a dynamic network cascade process developed by Duncan Watts applied to a class of random networks, developed independently by Newman and Miller, which allows a specified amount of clustering (short loops). We adapt existing methods for locally tree-like networks to formulate an appropriate two-type branching process to describe the spread of a cascade started with a single active node and obtain a fixed-point equation to implicitly express the extinction probability of such a cascade. In so doing, we also recover a formula that has appeared in various forms in works by Hackett et al. and Miller which provides a threshold condition for certain extinction of the cascade. We find that clustering impedes cascade propagation for networks of low average degree by reducing the connectivity of the network, but for networks with high average degree, the presence of small cycles makes cascades more likely.

Time bounded adaptive information coverage in social networks

In this paper, we study the time-bounded adaptive information coverage problem with myopic feedback (TBAIC) under a variant of the independent cascade (IC) model. In practical applications, time or deadline is a critical factor to evaluate the effectiveness of a strategy. Along this line, with considering deadline [Formula: see text], we sequentially select [Formula: see text] ([Formula: see text]) nodes as seed nodes, one at a time step, from a social network, and after a seed is selected at step [Formula: see text], it reveals the set of its activated neighbors, which will be valuable information for selecting subsequent seeds. On the other hand, during information propagation, if an active node fails to activate its neighbors, though not become active, those neighbors will know the information and may become active at a later step, we name them as covered nodes. In terms of information coverage, those covered nodes also make contributions. Therefore, our problem aims to choose a policy to maximize the expected cumulative number of both active and covered nodes throughout the time within deadline. We prove that our problem is adaptive monotone and adaptive submodular, which guarantees the adaptive greedy policy with myopic feedback to achieve an approximation ratio of [Formula: see text]. Additionally, we propose two algorithms to speed up the greedy policy.

An Active Node Switching Method Based on Discrete-Voltage Intervention for Seafloor Observation Network

The cabled seafloor observation network, which provides abundant power and broad bandwidth to seafloor scientific packages, has become one of the most efficient ocean exploration methods because of its long-term, real-time, and sustained presence. However, node failure or maintenance may shut down the system until the situation is cleared. An active node switching method based on discrete-voltage intervention is proposed to establish a reliable and robust underwater electrical network that allows the system to operate partially amid node failure or maintenance. This method switches a specific node on/off from the network whenever necessary. The main structure and operating mechanism of this switching method are presented in this paper. A prototype was established, and several tests were performed in a laboratory to validate its feasibility and reliability. The prototype was then integrated into a pool-testing underwater network that included a 50-km electrical/optical submarine cable between the base station and the junction box. The test results demonstrated that the active node-switching method can efficiently and reliably fix node failure emergency situations for cabled ocean networks.