Collaborative Research:CISE-MSI:RCBP-RF:CNS:RESCUE:Intelligent Public Safety based on Integrated Communications Systems
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1.EVACUSCAPE: Internet of Things-enabled emergency evacuation based on matching theory
- 关键词：
- Internet of Things; Evacuation process; Matching theory; Coalition games;SIMULATION; STRATEGY
- Atencio, Joshua R.;Siraj, Md Sadman;Tsiropoulou, Eirini Eleni
- 《INTERNET OF THINGS》
- 2025年
- 31卷
- 期
- 期刊
The effective evacuation during disaster scenarios, either physical or man-made, is critical in order to ensure the safety and survival of the victims, minimize the casualties, and facilitate the rapid and organized movement of people to safety. In this paper, the EVACUSCAPE model is introduced to optimize the matching between victims and evacuation routes during an evacuation process. Initially, the characteristics of both the victims and the evacuation routes are analyzed to establish a foundational matching mechanism among them. The Approximate EVACUSCAPE algorithm is developed to perform an initial matching between the victims and the evacuation routes by disregarding externalities that influence the victims' decisions, such as the actions of other evacuees. Then, the Accurate EVACUSCAPE algorithm refines the matching process by incorporating the principles of coalition games to account for these externalities and ultimately derive an optimal and stable evacuation strategy. A comprehensive evaluation using real-world datasets demonstrates the effectiveness and robustness of the EVACUSCAPE model, which significantly outperforms conventional evacuation strategies where the victims select routes based solely on proximity or time-optimization in a selfish manner.
...2.BRAVE: Benefit-aware data offloading in UAV edge computing using multi-agent reinforcement learning
- 关键词：
- Adversarial machine learning;Computation offloading;Reinforcement learning;Critical events;Cutting edges;Data offloading;Edge computing;Multi-agent reinforcement learning;Processing time;Public safety;Real time decision-making;Real-time decision making;Response management
- Pantaleon, Odyssefs Diamantopoulos;Rahman, Aisha B;Tsiropoulou, Eirini Eleni
- 《Simulation Modelling Practice and Theory》
- 2025年
- 140卷
- 期
- 期刊
Edge computing has emerged as a transformative technology in public safety and has the potential to support the rapid data processing and real-time decision-making during critical events. This paper introduces the BRAVE framework, a cutting-edge solution where the UAVs act as Mobile Edge Computing (MEC) servers, addressing users’ computational demands across disaster-stricken areas. An accurate UAV energy consumption model is introduced, including the UAV's travel, processing, and hover energy. BRAVE accounts for both the users’ Quality of Service (QoS) requirements, such as latency and energy constraints, and UAV energy limitations in order to determine the UAVs’ optimal path planning. The BRAVE framework consists of a two-level decision-making mechanism: a submodular game-based model ensuring the users’ optimal data offloading strategies, with provable Pure Nash Equilibrium properties, and a reinforcement learning-driven UAV path planning mechanism maximizing the data collection efficiency. Furthermore, the framework extends to collaborative multi-agent reinforcement learning (BRAVE-MARL), enabling the UAVs’ coordination for enhanced service delivery. Extensive experiments validate the BRAVE framework's adaptability and effectiveness and provide tailored solutions for diverse public safety scenarios. © 2025
...3.Symbiotic Positioning, Navigation, and Timing via Game Theory and Reinforcement Learning
- 关键词：
- Symbiosis; Timing; Reinforcement learning; Location awareness; Globalnavigation satellite system; Accuracy; Games; Reconfigurable intelligentsurfaces; Heuristic algorithms; Global Positioning System; Game theory;reconfigurable intelligent surfaces; reinforcement learning; symbioticpositioning; navigation; timing (SPNT);LOCALIZATION
- Siraj, Md Sadman;Tsiropoulou, Eirini Eleni;Papavassiliou, Symeon;Plusquellic, Jim
- 《IEEE ACCESS》
- 2025年
- 13卷
- 期
- 期刊
Precise positioning, navigation, and timing (PNT) capabilities are essential for numerous critical infrastructure systems and advanced location-dependent applications. The challenges related to the reliability and accuracy of traditional Global Navigation Satellite Systems (GNSS) have driven the pursuit of innovative alternative PNT methodologies. This paper presents a novel approach inspired by the concept of biological symbiosis and leveraging the advanced capabilities of Reconfigurable Intelligent Surfaces (RISs). The proposed framework establishes a cooperative interaction between targets with unknown positions and collaborator nodes with approximate location estimates. These interactions are supported by the RISs and the anchor nodes with known positions. The objective is to minimize errors in positioning and timing for both the targets and the collaborators. This challenge is modeled as a non-cooperative game, and the existence of a Nash Equilibrium is demonstrated using potential game theory. To solve the game, Best Response Dynamics and a log-linear Reinforcement Learning (RL)-based approach are developed to identify the equilibrium state. The proposed system is thoroughly evaluated through simulations, in order to demonstrate its performance and the key trade-offs between game-theoretic strategies and the RL-based solutions.
...4.CROWDMATCH: Optimizing Crowdsourcing Matching through the Integration of Matching Theory and Coalition Games
- 关键词：
- Crowdsourcing;Coalition game;Crowdmatching;Game-theoretic;Information availability;Information costs;Matching process;Matching theory;Matchings;System models;Utility functions
- Adesokan, Adedamola;Kinney, Rowan;Tsiropoulou, Eirini Eleni
- 《Future Internet》
- 2024年
- 16卷
- 2期
- 期刊
This paper tackles the challenges inherent in crowdsourcing dynamics by introducing the CROWDMATCH mechanism. Aimed at enabling crowdworkers to strategically select suitable crowdsourcers while contributing information to crowdsourcing tasks, CROWDMATCH considers incentives, information availability and cost, and the decisions of fellow crowdworkers to model the utility functions for both the crowdworkers and the crowdsourcers. Specifically, the paper presents an initial Approximate CROWDMATCH mechanism grounded in matching theory principles, eliminating externalities from crowdworkers’ decisions and enabling each entity to maximize its utility. Subsequently, the Accurate CROWDMATCH mechanism is introduced, which is initiated by the outcome of the Approximate CROWDMATCH mechanism, and coalition game-theoretic principles are employed to refine the matching process by accounting for externalities. The paper’s contributions include the introduction of the CROWDMATCH system model, the development of both Approximate and Accurate CROWDMATCH mechanisms, and a demonstration of their superior performance through comprehensive simulation results. The mechanisms’ scalability in large-scale crowdsourcing systems and operational advantages are highlighted, distinguishing them from existing methods and highlighting their efficacy in empowering crowdworkers in crowdsourcer selection. © 2024 by the authors.
...5.Stochastic financial analysis of diesel generation extension vs investment in hybrid photovoltaic-diesel-battery in a microgrid in the Amazon indigenous community
- 关键词：
- Cost effectiveness;Diesel engines;Economic analysis;Electric energy storage;Electric loads;Hybrid systems;Intelligent systems;Investments;Monte Carlo methods;Photoelectrochemical cells ;Renewable energy resources;Stochastic systems;Uncertainty analysis;Battery systems;Diesel generations;Diesel oil;Electricity supply;Financial analysis;Green electricity;Hybrid PV-diesel-battery system;Indigenous community;Monte Carlo's simulation;Stochastics
- Coelho, Eden de Oliveira Pinto;Aquila, Giancarlo;Bonatto, Benedito Donizeti;Nakamura, Wilson Toshiro;Rotella Junior, Paulo;Rocha, Luiz Célio Souza
- 《Energy for Sustainable Development》
- 2023年
- 77卷
- 期
- 期刊
Due to environmental, operational, and regional restrictions, Brazil still has a lot of communities that do not have an integrated electricity supply, however, the government aims to promote universal access to electricity in the country. In this way, diesel oil generators are the main electricity source for these isolated indigenous communities, but in the generation expansion planning, renewable energy sources are an important way to promote a more sustainable generation in these Amazon regions. This article aims to present an economic analysis based on a Cost-Effectiveness Analysis and Cost-Benefit Analysis, using the Monte Carlo Simulation that compares the extension of the diesel capacity versus a PV-diesel-battery (PVDB) system in the Maruwai indigenous community that is located in the state of Roraima (Brazil). The photovoltaic system and the battery storage system are considered an alternative instead of repowering the electricity supply of the increase in on-site diesel generator operation. The results show that the diesel breakeven price is far below the current diesel oil spot price, which indicates that the hybrid system with photovoltaic cells and batteries is more economically feasible. In turn, the stochastic analysis, the results indicate that the hybrid PVDB system is economically attractive, but needs political incentives to mitigate the uncertainties about the average return for the investor. © 2023 International Energy Initiative
...6.Alternative Positioning, Navigation, and Timing Enabled by Games in Satisfaction Form and Reconfigurable Intelligent Surfaces
- 关键词：
- Timing; Games; Global Positioning System; Shadow mapping; Globalnavigation satellite system; Reinforcement learning; Optimization;Positioning; navigation; and timing (PNT); reconfigurable intelligentsurfaces (RISs); reinforcement learning (RL); satisfaction games;LOCALIZATION; SELECTION; SYSTEMS; DESIGN; ERROR
- Siraj, Md Sadman;Rahman, Aisha B. B.;Diamanti, Maria;Tsiropoulou, Eirini Eleni;Papavassiliou, Symeon
- 《IEEE SYSTEMS JOURNAL》
- 2023年
- 卷
- 期
- 期刊
The potential degradation of the Global Positioning System and other Global Navigation Satellite Systems under several circumstances gives rise to the development of alternative position, navigation, and timing (PNT) technologies aiming at maintaining efficient and safe operations. In this article, we exploit the use of reconfigurable intelligent surfaces (RISs) as enablers for the design of an alternative PNT solution, with improved accuracy and efficiency. The specific problem of RISs' orchestration and configuration is treated via the adoption of game theory and reinforcement learning (RL). Initially, a satisfaction game is formulated and solved among the targets, enabling them to autonomously determine the optimal number of RISs that will contribute to their PNT service, while the specific set of RISs to be used is determined by a novel RL algorithm. In order to further maximize the received signal strength at each target of the reflected signals from the specific set of RISs, the phase-shift optimization of the latter is performed. Based on the above, an iterative least squares algorithm is adopted, following the multilateration technique, in order for each target to estimate its position and timing. The performance evaluation of the proposed approach is achieved via modeling and simulation.
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