Research Interest

In the last fifteen years, she has worked in the area of wireless communications and wireless networks. She has been attracted by the challenges of the pervasive and ubiquitous control of the physical environment, from the very beginning of this revolution. Methodologically, she is interested in modeling fundamental problems that arise in this context, with a particular attention to the optimization of the critical resources. She looks for rigorous solutions with high performance, and, whenever possible, the proposed solutions are experimentally tested.

Her recent contributes are in: networks of smart devices with special interest in energy aspects and security aspects, wireless sensor networks, content delivery in smart environments. The most recent topic is working on is the use of drones for efficiently solving basic problems in wireless sensor networks. One of the basic problems in the ubiquitous control of the physical environment that may take advantage from the use of drones is the localization of targets/sensors. The approach of replacing all the fixed anchors with a single drone that flies through a sequence of waypoints has been explored in order to speed-up and to minimize the cost of the localization (no cost for the anchors, no cost and no time for the deployment of the anchors). The problem presents novel aspects, which make existing localization algorithm and path planning algorithms unsuitable.

She has worked on sensor networks for more than ten years nowadays. She has almost always taken the view of a massive and random deployment of heterogeneous sensor devices — characterized by small size, low cost, extremely limited energy and anonymity — that cooperate with some distributed in-network control entities to guide the behaviour of the application end-users. In such a vision, she has studied the network ability of self-configuring and of working unattended. She has proposed unattended training algorithms in which the sensors learn their position in a lightweight coordinate system by means of an in-network sink. To save energy, she considered wireless duty-cycled sensor networks able to guarantee connectivity and data aggregation.In almost all results, a cost for switching between the awake and the sleep status in the energy model has been included to better fit the realistic energy model.

To study the ability of the wireless sensor network to collect information and to reply to query from the external world, she has studied the possibility to collect data in so-called storage nodes, that receive raw data from other nodes, compress them, and send them toward a sink. She studied the minimum k-storage problem, that is the problem of locating storage nodes in order to minimize the energy consumed for converging the raw data to the external word.

Mobile wireless devices, like smartphones, have catalyzed a lot of her attention since she thinks that the first real implementation of a massive random deployed network of sensors is that of the sensors embedded in the smart mobile devices we use every day. Due to the smartphone abilities in computing and communicating, smartphones consume a lot of energy and although smartphones are bigger than sensors, they experience the same scarcity of energy. She has investigated the possibility on smartphones of scheduling communications in pairs for minimizing the energy consumption. She has modeled the problem as a flow problem and a variant of the knapsack problem.

She hard worked to design efficient data-diffusion broadcast algorithms, which nowadays could be used to broadcast data in smart environments. She considered the problem of allocating N uniform data to K transmission channels so as the Average Expected Delay is minimized. The basic dynamic programming algorithm for solving the uniform allocation problem with cost O(N^2K) is speedup up to O(N K) time by applying a known optimal algorithm to find the row-minima of totally monotone matrices.

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