The Traveling Salesman Problem (TSP) is an important problem in computer science which consists in finding a path linking a set of cities so that each of then can be visited once, before the traveler comes back to the starting point. This is highly relevant because several real world problems can be mapped to it. A special case of TSP is the one in which the cities (the points to be visited) are not static as the cities, but mobile, changing their positions as the time passes. This variation is known as Moving Target TSP (MT-TSP). Emerging systems for crowd monitoring and control based on unmanned aerial vehicles (UAVs) can be mapped to this variation of the TSP problem, as a number of persons (targets) in the crowd can be assigned to be monitored by a given number of UAVs, which by their turn divide the targets among them. These target persons have to be visited from time to time, in a similar way to the cities in the traditional TSP. Aiming at finding a suitable solution for this type of crowd monitoring application, and considering the fact that exact solutions are too complex to perform in a reasonable time, this work explores and compares different heuristic methods for the intended solution. The performed experiments showed that the Genetic Algorithms present the best performance in finding acceptable solutions for the problem in restricted time and processing power situations, performing better compared to Ant Colony Optimization and Simulated Annealing Algorithms. (C) 2019 Published by Elsevier Ltd.
This article presents the development of a multi-unmanned aerial vehicle (UAV) based crowd monitoring system, demonstrating a system that uses UAVs to periodically monitor a group of moving walking individuals. Using auction paradigms to distribute targets among UAVs and genetic algorithms to calculate the best order to visit the targets, the system has shown capabilities to efficiently perform the surveillance, visiting all the targets during a surveillance period and minimizing the time between the visits made to each target. Moreover, the system showed robustness keeping the good performance under a variety of situations.
Complex cyber-physical systems can be difficult to analyze for resource adequacy (e.g., bandwidth and buffer size) at the concept development stage since relevant models are hard to create. During this period, details about the functions to be executed or the platforms in the architecture are partially unknown. This is especially true for Integrated Modular Avionics (IMA) systems, for which life-cycles span over several decades, with potential changes to functionality in the future. This work aims to identify abstractions for representing data exchanges among functions realized in networked IMA systems and investigates how these can be represented in formal models and analyzed with exact guarantees. Timed automata (TA) are a relevant choice for modeling since communication resource adequacy is directly related to potential network delays. We explore two alternatives in modeling with TA, a direct one representing every process using a TA template, and a more abstract one representing every computation device with a TA template. While the first approach represents process-to-process data exchanges, the modified approach reduces the state space by representing all processes currently allocated to a single computing element to obtain scalability gains. Both approaches are flexible since the templates presented can be instantiated to represent different types of network topologies and communication patterns. The instantiated TA models are used to illustrate an use case and analyzed with the UPPAAL model checker to verify that a given platform instance supports the desired system functions in terms of network bandwidth and buffer size adequacy, thereby messages reaching their final destination with freshness guarantees. Both abstraction levels are shown to be suitable for verifying the intended properties, but the more abstract one demonstrates a 67% improvement in verification time and a 66% reduction in state space during verification. The more abstract approach is also applied to a real-world example from an earlier publication, with a much larger state space and a more complex structure, to illustrate the ability to reuse the approach in multiple use cases. (C) 2021 The Authors. Published by Elsevier B.V.
Complex cyber-physical systems can be difficult to analyze for resource adequacy at the concept development stage since relevant models are hard to create. During this period, details about the functions to be executed or the platforms in the architecture are partially unknown. This is especially true for Integrated Modular Avionics (IMA) Systems, for which life-cycles span over several decades, with potential changes to functionality in the future. To support the engineers evaluating conceptual designs there is a need for tools that model resources of interest in an abstract manner and allow analyses of changing architectures in a modular and scalable way. This work presents a generic timed automata-based model of a networked IMA system abstracting complex networking and computational elements of an architecture, but representing the communication needs of each application function using UPPAAL templates. The proposed model is flexible and can be modified/extended to represent different types of network topologies and communication patterns. More specifically, the different components of the IMA network, Core Processing Modules, Network End-Systems, and Switches, are represented by different templates. The templates are then instantiated to represent a conceptual design, and fed into a model checker to verify that a given platform instance supports the desired system functions in terms of network bandwidth and buffer size adequacy - in particular, whether messages can reach their final destination on time. The work identifies the limits of the tool used for this evaluation, but the conceptual model can be carried over to other tools for further studies.