Ricerc@Sapienza

This paper presents two dynamic and distributed clustering algorithms for Wireless Sensor Networks (WSNs). Clustering approaches are used in WSNs to improve the network lifetime and scalability by balancing the workload among the clusters. Each cluster is managed by a cluster head (CH) node. The first algorithm requires the CH nodes to be mobile: by dynamically varying the CH node positions, the algorithm is proved to converge to a specific partition of the mission area, the generalised Voronoi tessellation, in which the loads of the CH nodes are balanced.

Routing solutions for multi-hop underwater wireless sensor networks suffer significant performance degradation as they fail to adapt to the overwhelming dynamics of underwater environments. To respond to this challenge, we propose a new data forwarding scheme where relay selection swiftly adapts to the varying conditions of the underwater channel.

With the ever-growing usage of batteries in the IoT era, the need for more eco-friendly technologies is clear. RF-powered computing enables the re-design of personal computing devices in a battery-less manner. While there has been substantial work on the underlying methods for RF-powered computing, practical applications of this technology has largely been limited to scenarios that involve simple tasks. This article demonstrates how RFID technology, typically used to implement object identification and counting, can be exploited to realize a battery-free Smart Home.

The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symmetric networks, i.e. α=1.

In this work, we have investigated the concept of “restraining bolt”, inspired by Science Fiction. We have two distinct sets of features extracted from the world, one by the agent and one by the authority imposing some restraining specifications on the behaviour of the agent (the “restraining bolt”). The two sets of features and, hence the model of the world attainable from them, are apparently unrelated since of interest to independent parties. However, they both account for (aspects of) the same world.

Ethology has shown that animal groups or colonies can solve complex problems distributing

Software implementations of neuronal systems have demonstrated their great effectiveness in managing and analyzing large amounts of data. While performing various signal processing tasks such as image processing, artificial intelligence and deep learning, neural software has limitations that derive from the characteristic structural division between processing and memory. To overcome such limitations, computing research has moved towards the realization of neuromorphic hardware models.