arXiv subjects

Georgios Diamantopoulos

Publications and source records attributed to Georgios Diamantopoulos.

7 recordsLinked to original sources

arXiv2026

TwinLoop: Simulation-in-the-Loop Digital Twins for Online Multi-Agent Reinforcement Learning

Decentralised online learning enables runtime adaptation in cyber-physical multi-agent systems, but when operating conditions change, learned policies often require substantial trial-and-error interaction before recovering performance. To address this, we propose TwinLoop, a simulation-in-the-loop digital twin framework for online multi-agent reinforcement learning. When a context shift occurs, the digital twin is triggered to reconstruct the current system state, initialise from the latest agent policies, and perform accelerated policy improvement with simulation what-if analysis before synchronising updated parameters back to the agents in the physical system. We evaluate TwinLoop in a vehicular edge computing task-offloading scenario with changing workload and infrastructure conditions. The results suggest that digital twins can improve post-shift adaptation efficiency and reduce reliance on costly online trial-and-error.

cs.LG↗

arXiv2025

Decentralised Blockchain Management Through Digital Twins

The necessity of blockchain systems to remain decentralised limits current solutions to blockchain governance and dynamic management, forcing a trade-off between control and decentralisation. In light of the above, this work proposes a dynamic and decentralised blockchain management mechanism based on digital twins. To ensure decentralisation, the proposed mechanism utilises multiple digital twins that the system's stakeholders control. To facilitate decentralised decision-making, the twins are organised in a secondary blockchain system that orchestrates agreement on, and propagation of decisions to the managed blockchain. This enables the management of blockchain systems without centralised control. A preliminary evaluation of the performance and impact of the overheads introduced by the proposed mechanism is conducted through simulation. The results demonstrate the proposed mechanism's ability to reach consensus on decisions quickly and reconfigure the primary blockchain with minimal overhead.

cs.CR↗

arXiv2024

Dynamic Digital Twins of Blockchain Systems: State Extraction and Mirroring

Blockchain adoption is reaching an all-time high, with a plethora of blockchain architectures being developed to cover the needs of applications eager to integrate blockchain into their operations. However, blockchain systems suffer from the trilemma trade-off problem, which limits their ability to scale without sacrificing essential metrics such as decentralisation and security. The balance of the trilemma trade-off is primarily dictated by the consensus protocol used. Since consensus protocols are designed to function well under specific system conditions, and consequently, due to the blockchain's complex and dynamic nature, systems operating under a single consensus protocol are bound to face periods of inefficiency. The work presented in this paper constitutes part of an effort to design a Digital Twin-based blockchain management framework to balance the trilemma trade-off problem, which aims to adapt the consensus process to fit the conditions of the underlying system. Specifically, this work addresses the problems of extracting the blockchain system and mirroring it in its digital twin by proposing algorithms that overcome the challenges posed by blockchains' decentralised and asynchronous nature and the fundamental problems of global state and synchronisation in such systems. The robustness of the proposed algorithms is experimentally evaluated.

cs.CR↗

arXiv2024

Large Language Models for Explainable Decisions in Dynamic Digital Twins

Dynamic data-driven Digital Twins (DDTs) can enable informed decision-making and provide an optimisation platform for the underlying system. By leveraging principles of Dynamic Data-Driven Applications Systems (DDDAS), DDTs can formulate computational modalities for feedback loops, model updates and decision-making, including autonomous ones. However, understanding autonomous decision-making often requires technical and domain-specific knowledge. This paper explores using large language models (LLMs) to provide an explainability platform for DDTs, generating natural language explanations of the system's decision-making by leveraging domain-specific knowledge bases. A case study from smart agriculture is presented.

cs.AI↗

arXiv2024

Distributed Simulation for Digital Twins of Large-Scale Real-World DiffServ-Based Networks

Digital Twin technology facilitates the monitoring and online analysis of large-scale communication networks. Faster predictions of network performance thus become imperative, especially for analysing Quality of Service (QoS) parameters in large-scale city networks. Discrete Event Simulation (DES) is a standard network analysis technology, and can be further optimised with parallel and distributed execution for speedup, referred to as Parallel Discrete Event Simulation (PDES). However, modelling detailed QoS mechanisms such as DiffServ requires complex event handling for each network router, which can involve excessive simulation events. In addition, current PDES for network analysis mostly adopts conservative scheduling, which suffers from excessive global synchronisation to avoid causality problems. The performance analysis of optimistic PDES for real-world large-scale network topology and complex QoS mechanisms is still inadequate. To address these gaps, this paper proposes a simulation toolkit, Quaint, which leverages an optimistic PDES engine ROSS, for detailed modelling of DiffServ-based networks. A novel event-handling model for each network router is also proposed to significantly reduce the number of events in complex QoS modelling. Quaint has been evaluated using a real-world metropolitan-scale network topology with 5,000 routers/switches. Results show that compared to the conventional simulator OMNeT++/INET, even the sequential mode of Quaint can achieve a speedup of 53 times, and the distributed mode has a speedup of 232 times. Scalability characterisation is conducted to portray the efficiency of distributed execution, and the results indicate the future direction for workload-aware model partitioning.

cs.DC↗

arXiv2023

Dynamic Data-Driven Digital Twins for Blockchain Systems

In recent years, we have seen an increase in the adoption of blockchain-based systems in non-financial applications, looking to benefit from what the technology has to offer. Although many fields have managed to include blockchain in their core functionalities, the adoption of blockchain, in general, is constrained by the so-called trilemma trade-off between decentralization, scalability, and security. In our previous work, we have shown that using a digital twin for dynamically managing blockchain systems during runtime can be effective in managing the trilemma trade-off. Our Digital Twin leverages DDDAS feedback loop, which is responsible for getting the data from the system to the digital twin, conducting optimisation, and updating the physical system. This paper examines how leveraging DDDAS feedback loop can support the optimisation component of the trilemma benefiting from Reinforcement Learning agents and a simulation component to augment the quality of the learned model while reducing the computational overhead required for decision-making.

cs.CR↗

arXiv2022

Digital Twins for Dynamic Management of Blockchain Systems

Blockchain systems are challenged by the so-called Trilemma tradeoff: decentralization, scalability and security. Infrastructure and node configuration, choice of the Consensus Protocol and complexity of the application transactions are cited amongst the factors that affect the tradeoffs balance. Given that Blockchains are complex, dynamic dynamic systems, a dynamic approach to their management and reconfiguration at runtime is deemed necessary to reflect the changes in the state of the infrastructure and application. This paper introduces the utilisation of Digital Twins for this purpose. The novel contribution of the paper is design of a framework and conceptual architecture of a Digital Twin that can assist in maintaining the Trilemma tradeoffs of time critical systems. The proposed Digital Twin is illustrated via an innovative approach to dynamic selection of Consensus Protocols. Simulations results show that the proposed framework can effectively support the dynamic adaptation and management of the Blockchain

cs.CR↗