Consensus - loosely defined as global agreement on the state of a decentralised network across its mutually untrusting participants - is an essential ingredient for decentralisation. At the same time, its scalability remains the Achilles' heel of distributed systems. A number of ongoing R&D efforts aim at scaling blockchain networks up to hundreds of thousands of transactions per second. Yet even such performance targets can be seen as modest when the goal is to bring traditional web workloads to the decentralised web (Web3), requiring the handling of billions of transactions per second, large volumes of data, complex workloads and applications, and hard latency requirements. The goal of this workshop is to foster scientific exchange across a wider community in consensus research and adjacent fields, by disseminating and providing a forum for discussion of upcoming impactful research with a practical twist.

The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors - upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.

Robotic odor source localization is a promising tool with numerous applications in safety, search and rescue, and environmental science. In this paper, we present an algorithm for odor source localization using multiple cooperating robots equipped with chemical sensors. Laplacian feedback is employed to maintain the robots in a formation, introducing spatial diversity that is used to better establish the position of the flock relative to the plume and its source. Robots primarily move upwind but use odor information to adjust their position and spacing so that they are centered on the plume and trace its structure. Real-world experiments were performed with an ethanol plume inside a wind tunnel, and used to both validate the algorithm and assess the impact of different formation shapes.

The use of groups of autonomous marine vehicles has enormous potential in numerous marine applications, perhaps the most relevant of which is the surveying and exploration of the oceans, still widely unknown and misunderstood. In many mission scenarios requiring the concerted operation of multiple marine vehicles carrying distinct, yet complementary sensor suites, relative positioning and formation control becomes mandatory. However, the constraints placed by the medium make it hard to both communicate and localize vehicles, even in relation to each other. In this paper, we deal with the challenging problem of keeping an autonomous underwater vehicle in a moving triangular formation with respect to 2 leader vehicles. We build upon our previous theoretical work on range-only formation control, which presents simple feedback laws to drive the controlled vehicle to its intended position in the formation using only ranges obtained to the leading vehicles with no knowledge of the formation path. We then introduce the real-world constraints associated with the use of autonomous underwater vehicles, especially the low frequency characteristics of acoustic ranging and its unreliability. We discuss the required changes to implement the solution in our vehicles, and provide simulation results using a full dynamic and communication model. Finally, we present the results of real world trials using MEDUSA-class autonomous marine vehicles.

A flexible Wireless Sensor Network platform for easier implementation of diverse applications has been developed and deployed at one of the Institute Superior Tecnico - Technical University of Lisbon (IST-TUL) campus. Since its initial deployment in 2007, this test-bed has grown steadily, supporting new nodes, applications and experiments. However, some initial problems, which were solved on an ad hoc basis, are becoming more serious as the network spans throughout the campus. Major issues, like global power management, have to be tackled not only with traditional protocol level approaches but also from a system's viewpoint, providing solutions that are capable of guaranteeing a consistent operational test-bed. We discuss the main issues related with the development of power management solutions, at different levels, presenting our architecture, design choices and implementation. We also address the lessons learnt from its integration in the platform. Results of the experimental evaluation of our solution have shown considerable energy savings (extending the network lifetime up to 9 times) even in the presence of demanding applications.