Wireless sensor networks (WSN) are being increasingly used for data acquisition and control of remote devices. However, they present some constraints in critical and large-scale scenarios. The main limitations come from the nature of their components, such as lossy links, and devices with power supply limitations, poor processing power and limited memory. The main feature of software-defined networks (SDN) is the separation between the control plane and the data plane, making available a logically unified view of the topology in the controllers. In this way, it is possible to build network applications that take into account this unified view, which makes the SDN an alternative approach to solve the mentioned limitations. This paper presents the SD6WSN (software-defined 6LoWPAN wireless sensor network) architecture, developed to control the behavior of the data traffic in 6LoWPAN according to the SDN approach. It takes into account the specific characteristics of WSN devices, such as low data transfer rate, high latency, packet loss and low processing power, and takes advantage of the flexibility provided by flow-based forwarding, allowing the development of specific networking applications based on a unified view. We provide a detailed description of how we have implemented SD6WSN in the Contiki operating system. The new architecture is assessed in two experiments. The first considers a typical advanced metering infrastructure (AMI) network and measures the overhead of SD6WSN control messages in configurations involving different path lengths. The results indicate that the overhead introduced is not excessive, given the advantages that the SDN approach can bring. The second considers a grid-topology to evaluate the average latency of the peer-to-peer communication. It was observed that the average latency in the SD6WSN is considerably lower than that obtained with standard 6LoWPAN, showing the potential of the proposed approach.

Direct-to-satellite Internet of Things (IoT) solutions have attracted a lot of attention from industry and academia recently, as promising alternatives for large scale coverage of a massive number of IoT devices. In this work, we considered that a cluster of IoT devices was under the coverage of a constellation of low-Earth orbit (LEO) satellites, while slotted Aloha was used as a medium access control technique. Then, we analyzed the throughput and packet loss rate while considering potentially different erasure probabilities at each of the visible satellites within the constellation. We show that different combinations of erasure probabilities at the LEO satellites and the IoT traffic load can lead to considerable differences in the system’s performance. Next, we introduce an intelligent traffic load distribution (ITLD) strategy, which, by choosing between a non-uniform allocation and the uniform traffic load distribution, guarantees a high overall system throughput, by allocating more appropriate amounts of traffic load at different positions (i.e., different sets of erasure probabilities) of the LEO constellation with respect to the IoT cluster. Finally, the results show that ITLD, a mechanism with low implementation complexity, allows the system to be much more scalable, intelligently exploiting the potential of the different positions of the satellite constellation.

Smart Utility Networks (SUN) rely on the Wireless-SUN (Wi-SUN) specification for years. Recently practitioners and researchers have considered Low-Power Wide-Area Networks (LPWAN) like LoRa WAN for SUN applications. With distinct technologies deployed in the same area and sharing unlicensed bands, one can expect these networks to interfere with one another. This paper builds over a LoRa WAN model to optimize network parameters while accounting for inter-technology interference. Our analytic model accounts for the interference LoRa WAN receives from IEEE 802.15.4G networks, which forms the bottom layers of Wi-SUN systems. We derive closed-form equations for the expected reliability of LoRa WAN in such scenarios. We set the model parameters with data from real measurements of the interplay among the technologies. Finally, we propose two optimization algorithms to determine the best LoRaWAN configurations, given a targeted minimum reliability level. The algorithms maximize either communication range or the number of users given constraints on the minimum number of users, minimum communication range, and minimum reliability. We validate the models and algorithms through numerical analysis and simulations. The proposed methods are useful tools for planning interference-limited networks with requirements of minimum reliability.

Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing.

The use of monitoring sensors is increasingly present in the context of precision agriculture. Usually, these sensor nodes (SNs) alternate their states between periods of activation and hibernation to reduce battery usage. When employing unmanned aerial vehicles (UAVs) to collect data from SNs distributed over a large agricultural area, we must synchronize the UAV route with the activation period of each SN. In this article, we address the problem of optimizing the UAV path through all the SNs to reduce its flight time, while also maximizing the SNs’ lifetime. Using the concept of timeslots for time base management combined with the idea of flight prohibition list, we propose an efficient algorithm for discovering and reconfiguring the activation time of the SNs. Experimental results were obtained through the development of our own simulator—UAV Simulator. These results demonstrate a considerable reduction in the distance traveled by the UAV and also in its flight time. In addition, the model provides a reduction in transmission time by SNs after reconfiguration, thus ensuring a longer lifetime for the SNs in the monitoring environment, as well as improving the freshness and continuity of the gathered data, which support the decision-making process.