Software-defined networking (SDN) was devised to simplify network management and automate infrastructure sharing in wired networks. These benefits motivated the application of SDN in resource-constrained wireless networks to leverage solutions for complex applications. However, some of the core SDN traits expose the networks to Denial-of-Service (DoS) attacks. There are proposals in the literature to detect DoS in wireless SDN networks; however, not without shortcomings: there is little focus on resource constraints, high detection rates have been reported mostly for small networks and the detection is disengaged from the identification of the type of attack or the attacker. Our work targets these shortcomings by introducing a lightweight, online change point detector to monitor performance metrics that are impacted when the network is under attack. A key novelty is that the proposed detector is able to operate in either centralized or distributed mode. The centralized detector has very high detection rates and can further distinguish the type of attack from a list of known attacks. In turn, the distributed detector can be useful to identify the nodes launching the attack. Our proposal is tested over IEEE 802.15.4 networks. The results show detection rates exceeding 96% in networks of 36 and 100 nodes and identification of the type of attack with a probability exceeding 89% when using the centralized approach.

Software-Defined Networking is a promising paradigm for providing flexibility and programmability to computer networks. Our goal is to assess the performance of this paradigm applied to Wireless Sensor Networks. Previous evaluations are not complete, since they study small networks, do not explore crucial performance metrics, or solely examine light traffic conditions. For this, we execute simulations and a testbed experiment. The testbed shows Software-Defined Networking successfully operates in a real network. We study simulated networks up to 289 data-transmitting nodes, while assessing all the main networks metrics: data delivery, delay, control overhead, and energy consumption. We investigate important parameters for Software-Defined Wireless Sensor Networks, such as controller positioning, radio duty cycling, number of data sinks, and use of source routed control messages. The results indicate that Software-Defined Networking is feasible forWireless Sensor Networks, presenting competitive data delivery ratio while saving energy in comparison to RPL, the Routing Protocol for Low-power and lossy networks.

Resource Constraints in Wireless Sensor Networks are a key factor in protocols and application design. Furthermore, energy consumption plays an important role in protocols decisions, such as routing metrics. In Software-Defined Networking (SDN)-based networks, the controller is in charge of all control and routing decisions. Using energy as a metric requires such information from the nodes, which would increase packets traffic, impacting the network performance. Previous works have used energy prediction techniques to reduce the number of packets exchanged in traditional distributed routing protocols. We applied this technique in Software-Defined Wireless Sensor Networks (SDWSN). For this, we implemented an energy prediction algorithm for SDWSN using Markov chain. We evaluated its performance executing the prediction on every node and on the SDN controller. Then, we compared their results with the case without prediction. Our results showed that by running the Markov chain on the controller we obtain better prediction and network performance than when running the predictions on every node. Furthermore, we reduced the energy consumption for topologies up to 49 nodes for the case without prediction.

Wireless Sensor Networks (WSN) are key enablers for several applications such as smart agriculture and smart cities. Software Defined Wireless Sensor Networking (SDWSN) paradigm improves WSN resource sharing, flexibility, and management. Monitoring network performance is essential to network management and it also plays an important role in making better use of scarce resources. However, obtaining network performance metrics in WSN is not trivial due to energy and computational constraints on the WSN nodes. The main contribution of this paper is a performance monitoring module for IT-SDN, an SDWSN framework. This module collects information about the data packets transmitted, queue delay and available energy on the WSN nodes, and sends the information as requested by the controller. The results showed that the monitoring module neither impacts the delivery rate, delay and overhead of the network, nor the energy consumption of the node. Also, the data collected by the monitoring module is pretty similar to the real values.

In the Electrical Engineering undergraduate program of the University of Costa Rica, most of the design and analysis projects are guided, structured and related to a specific topic, limiting technical content and machining the way problems are solved, which in turn, restricts the motivated student creativity. The ElectrizArte Project provides the opportunity to develop both technical and not-technical skills in a extracurricular enviroment. As the main theme, ElectrizArte allows students to design, implement, and operate projects that combine engineering with art, taking advantage of the particular situation that many of the students participating in the project, have interest in art in general, or practice some artistic activity.