The unprecedented capabilities of monitoring and responding to stimuli in the physical world of wireless sensor and actuator networks (WSAN) enable these networks to provide the underpinning for several Smart City applications, such as structural health monitoring (SHM). In such applications, civil structures, endowed with wireless smart devices, are able to self-monitor and autonomously respond to situations using computational intelligence. This work presents a decentralized algorithm for detecting damage in structures by using a WSAN. As key characteristics, beyond presenting a fully decentralized (in-network) and collaborative approach for detecting damage in structures, our algorithm makes use of cooperative information fusion for calculating a damage coefficient. We conducted experiments for evaluating the algorithm in terms of its accuracy and efficient use of the constrained WSAN resources. We found that our collaborative and information fusion-based approach ensures the accuracy of our algorithm and that it can answer promptly to stimuli (1.091 s), triggering actuators. Moreover, for 100 nodes or less in the WSAN, the communication overhead of our algorithm is tolerable and the WSAN running our algorithm, operating system and protocols can last as long as 468 days.

This paper proposes a framework for embedding a software watermark using obfuscation and tamper-proofing techniques, called SensorWatermark in order to inhibit piracy of embedded software in sensor nodes in a WSN. The watermark scheme proposed is characterized as an ordered sequence of obfuscations and guards implemented in the software, where such sequence identifies the software author. SensorWatermark is able to correctly identify the author from the embedded watermark and does not affect negatively the constrained resources of a sensor device. Finally, SensorWatermark is resilient and stealthy to certain attacks, as demonstrated in the experiments.

This paper presents FraSEE, a framework whose goal is to increase the energy efficiency (EE) of smart grid applications, specifically for the Power Quality (PQ) application domain. The key idea is to use a Wireless Sensor and Actuator Network (WSAN) and decentralize the decision processes of such applications among WSAN nodes through information fusion. Experiments assessed FraSEE effectiveness in increasing the EE of a PQ application, its accuracy, i.e. correct PQ disturbance detections, considering the influence of environmental parameters in decision process, its overhead, i.e. WSAN resources consumption; and delay for performing control actions in response to decisions.

This work presents an adaptation (and enhancement) of a well-known fusion technique in order to deal with multiple applications simultaneously in a context of Shared Sensor and Actuator Networks (SSAN). SSAN allow the sensing infrastructure to be shared among multiple applications that can potentially belong to different users instead of assuming an application-specific network design. We also present simulation and tests conducted with the proposed solution on real nodes to validate our proposal.

Developing Wireless Sensor Networks (WSN) applications is not an easy task, since it demands different expertise and knowledge. To address this problem, we propose a model-driven approach to build WSN applications. It promotes the separation of concerns between two levels of requirements involved: (i) domain experts, with no knowledge on WSN platforms, contribute to the development of applications, (ii) network experts, with no knowledge on the application domain, program nodes to meet application requirements. Our approach also promotes the reuse of software artifacts: an application model can be reused on different sensor platforms and a platform model can be reused for different WSN applications.

This work presents an algorithm that aims at maximizing the network efficiency while meeting QoS requirements for different classes of users mobile in a scenario that supports the integration of wireless broadband networks such as WiMAX. The presented algorithm exploits the behavior of the mobile user, depicted in a user profile, for (i) refining the set of cells foreseen for the next handover process, taking into account the class of user as well as both the service and the network contexts, and (ii) proactive reserving resources for the cell chosen for the next handover. This algorithm is validated through an extensive simulation approach, corroborating the expected improvements.

We propose a fuzzy-based decision-making mechanism for selecting data dissemination protocols in wireless sensor networks (WSNs). Its goal is to select the most efficient protocol considering network performance and application-specific requirements. The mechanism relies on performing simulations and on defining and executing a two-tier fuzzy system. First, well-known WSN protocols are simulated over different scenarios and application requirements to feed a knowledge base. Then, a set of fuzzy systems are built based on the simulation results. A methodology for guiding the building of the knowledge base was developed. A case study is described to validate the mechanism and demonstrate its employment and usefulness.