Smart Contracts-Enabled Simulation for Hyperconnected Logistics

Betti, Quentin; Montreuil, Benoît; Khoury, Raphaël; Hallé, Stéphane

doi:10.1007/978-3-030-38677-1_6

Cited by 7 publications

(5 citation statements)

References 47 publications

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“…Overall, one can conclude that the overhead incurred by the use of the pipeline is reasonable. For instance, in a real-world setting such as a blockchain, the limiting factor is more likely to be the number of transactions per second supported by the infrastructure itself; as a single example, the Ethereum network handles at most a few dozen transactions per second on the main net [4]. On its side, memory overhead remains relatively low with a few kilobytes, with a maximum demand of about 120 kB for a single scenario.…”

Section: Implementation and Experimental Resultsmentioning

confidence: 99%

A Modular Runtime Enforcement Model Using Multi-traces

Taleb

Hallé

Khoury

2022

Lecture Notes in Computer Science

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Runtime enforcement seeks to provide a valid replacement to any misbehaving sequence of events of a running system so that the correct sequence complies with a user-defined security policy. However, depending on the capabilities of the enforcement mechanism, multiple possible replacement sequences may be available, and the current literature is silent on the question of how to choose the optimal one. In this paper, we propose a new model of enforcement monitors, that allows the comparison between multiple alternative corrective enforcement actions and the selection of the optimal one, with respect to an objective user-defined gradation, separate from the security policy. These concepts are implemented using the event stream processor BeepBeep and a use case is presented. Experimental evaluation shows that our proposed framework can dynamically select enforcement actions at runtime, without the need to manually define an enforcement monitor.

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Section: Implementation and Experimental Resultsmentioning

confidence: 99%

A Modular Runtime Enforcement Model Using Multi-traces

Taleb

Hallé

Khoury

2022

Lecture Notes in Computer Science

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“…Blockchain technology is showing good potential in connecting data(bases), because of its distinguishing advantage in handling data privacy and security, and responsibility tracking (Hofmann and Rüsch, 2017). It is foreseeable that smart contract technology that can automate agreement-based processes will further promote the application of blockchain in autonomous and self-organizing logistics systems and enhance the added value (Betti et al, 2020(Betti et al, , 2019Christidis and Devetsikiotis, 2016). According to Wang et al (2019), smart contracts will prevail in supply chain collaborations and ecosystems, as a result of their particular advantage for decentralized collaboration.…”

Section: Autonomous and Self-organizing Logistics Systemsmentioning

confidence: 99%

Digital interoperability in logistics and supply chain management: state-of-the-art and research avenues towards Physical Internet

Pan

Trentesaux

McFarlane

et al. 2021

Computers in Industry

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“…It develops a Blockchain‐based 4‐layered framework to overcome some of the barriers within PI associated with the exchange of value and physical assets in decentralized logistics networks. Betti et al (2019a, 2019b) investigate the exploitation of Blockchain distributed ledgers and smart contracts in interconnected logistics and validate the potential by coupling an agent‐oriented discrete‐events simulation with a Blockchain platform. In the same vein, Tran‐Dang et al (2020) investigate the application of Internet of Things technologies, building blocks, and a service‐oriented architecture to accelerate the implementation of PI.…”

Section: Recent Research About Physical Internetmentioning

confidence: 99%