Distributed estimation and control of node centrality in undirected asymmetric networks

Measures of node centrality that describe the importance of a node within a network are crucial for understanding the behavior of social networks and graphs. In this paper, we address the problems of distributed estimation and control of node centrality in undirected graphs with asymmetric weight values. In particular, we focus our attention on $\alpha$-centrality, which can be seen as a generalization of eigenvector centrality. In this setting, we first consider a distributed protocol where agents compute their $\alpha$-centrality, focusing on the convergence properties of the method; then, we combine the estimation method with a consensus algorithm to achieve a consensus value weighted by the influence of each node in the network. Finally, we formulate an $\alpha$-centrality control problem which is naturally decoupled and, thus, suitable for a distributed setting and we apply this formulation to protect the most valuable nodes in a network against a targeted attack, by making every node in the network equally important in terms of {\alpha}-centrality. Simulations results are provided to corroborate the theoretical findings.Comment: published on IEEE Transactions on Automatic Control https://ieeexplore.ieee.org/abstract/document/912618

Network Localization by Shadow Edges

Localization is a fundamental task for sensor networks. Traditional network construction approaches allow to obtain localized networks requiring the nodes to be at least tri-connected (in 2D), i.e., the communication graph needs to be globally rigid. In this paper we exploit, besides the information on the neighbors sensed by each robot/sensor, also the information about the lack of communication among nodes. The result is a framework where the nodes are required to be bi-connected and the communication graph has to be rigid. This is possible considering a novel typology of link, namely Shadow Edges, that account for the lack of communication among nodes and allow to reduce the uncertainty associated to the position of the nodes.Comment: preprint submitted to 2013 European Control Conference, July 17-19 2013, Zurich, Switzerlan

A Sum-of-States Preservation Framework for Open Multi-Agent Systems With Nonlinear Heterogeneous Coupling

In this paper, we develop a general Open Multi-Agent Systems (OMAS) framework over undirected graphs where the agents' interaction is, in general, nonlinear, time-varying, and heterogeneous, in that the agents interact with different pairwise interaction rules for each link, possibly nonlinear, which may change over time. In particular, assuming the agents interact by exchanging flows , which modify their states, our framework guarantees that the sum of the states of agents participating to the network is preserved. To this end, agents maintain a state variable for each of their neighbors. Upon disconnection of a neighbor, such a variable is used to completely eliminate the effect of previous interaction with disconnected agents from the overall systems. In order to demonstrate the effectiveness of the proposed OMAS framework, we provide a case study focused on average consensus, and, specifically, we develop a sufficient condition on the structure of the agents' interaction guaranteeing asymptotic convergence under the assumption that the network becomes fixed. The paper is complemented by simulation results that numerically demonstrate the effectiveness of the proposed method

Estimation of damping through internally excited roll tests

Roll damping represents a key factor for a proper estimation of the ship behaviour in a seaway. However, due to the typical dominance of viscous effects, accurately estimating roll damping is a challenging task. The most common experimental approach for determining roll damping parameters is based on the analysis of roll decays, although forced and excited roll tests in calm water or in waves have been used as well. This paper proposes a technique for estimating roll damping from internally excited roll tests in calm water. Tests are performed by exciting roll motion through an internal shifting mass. Roll damping parameters can then be determined from the analysis of the obtained roll response curves. The paper describes the experimental technique and a nonlinear mathematical model for representing the system dynamics. A procedure is proposed for determining roll damping coefficients, using, as a basis for the analysis, the developed mathematical model. A case study is reported where damping coefficients are determined for a trawler fishing vessel using the proposed technique. Obtained results are compared with those from standard roll decays analysis. For model validation purposes, the experimental roll response curves are also compared with those simulated through the developed mathematical model

Managing the far-Edge: are today's centralized solutions a good fit

Edge computing has established itself as the foundation for next-generation mobile networks, IT infrastructure, and industrial systems thanks to promised low network latency, computation offloading, and data locality. These properties empower key use-cases like Industry 4.0, Vehicular Communication and Internet of Things. Nowadays implementation of Edge computing is based on extensions to available Cloud computing software tools. While this approach accelerates adoption, it hinders the deployment of the aforementioned use-cases that requires an infrastructure largely more decentralized than Cloud data centers, notably in the far-Edge of the network. In this context, this work aims at: (i) to analyze the differences between Cloud and Edge infrastructures, (ii) to analyze the architecture adopted by the most prominent open-source Edge computing solutions, and (iii) to experimentally evaluate those solutions in terms of scalability and service instantiation time in a medium-size far Edge system. Results show that mainstream Edge solutions require powerful centralized controllers and always-on connectivity, making them unsuitable for highly decentralized scenarios in the far-Edge where stable and high-bandwidth links are not ubiquitous.This work has been partially funded by the H2020 collaborative Europe/Taiwan research project 5G-DIVE (grant no. 589881) and by the H2020 European collaborative research project DAEMON (grant no. 101017109)

Edge Robotics: are we ready? An experimental evaluation of current vision and future directions

Cloud-based robotics systems leverage a wide range of Information Technologies (IT) to offer tangible benefits like cost reduction, powerful computational capabilities, data offloading, etc. However, the centralized nature of cloud computing is not well-suited for a multitude of Operational Technologies (OT) nowadays used in robotics systems that require strict real-time guarantees and security. Edge computing and fog computing are complementary approaches that aim at mitigating some of these challenges by providing computing capabilities closer to the users. The goal of this work is hence threefold: i) to analyze the current edge computing and fog computing landscape in the context of robotics systems, ii) to experimentally evaluate an end-to-end robotics system based on solutions proposed in the literature, and iii) to experimentally identify current benefits and open challenges of edge computing and fog computing. Results show that, in the case of an exemplary delivery application comprising two mobile robots, the robot coordination and range can be improved by consuming real-time radio information available at the edge. However, our evaluation highlights that the existing software, wireless and virtualization technologies still require substantial evolution to fully support edge-based robotics systems.This work has been partially funded by European Union’s Horizon 2020 research and innovation programme under grant agreement No 101015956, and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union- NextGenerationEU through the UNICO 5G I+ D 6G-EDGEDT and 6G-DATADRIVE