Agent Directed HLA Simulation for Complex Supply Chain Modeling

Bruzzone, Agostino G.; Mosca, Roberto; Revetria, Roberto; Bocca, Enrico; Briano, Enrico

doi:10.1177/0037549704047602

Cited by 26 publications

(6 citation statements)

References 5 publications

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“…SCs are CAS because they have some subsystems with agency characteristics (e.g. intelligent goods and resources [humans, machineries, organizations]) that are able to intervene meaningfully in the course of events, or, as Bruzzone et al (2005) highlight, because they sense and re-act to external stimuli. Complex adaptive SCs, or networks, are comprised of heterogeneous interacting agents that work under quasi-equilibrium (Li et al, 2010) and a combination of regularity and randomness (Surana et al, 2005).…”

Section: Complexity Properties Of Supply Chain Systemsmentioning

confidence: 99%

Steering supply chains from a complex systems perspective

Abbasi¹,

Varga²

2022

EJMS

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PurposeThe purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.Design/methodology/approachThe research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.FindingsThe main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.Originality/valueRecognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

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Section: Complexity Properties Of Supply Chain Systemsmentioning

confidence: 99%

Steering supply chains from a complex systems perspective

Abbasi¹,

Varga²

2022

EJMS

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“…The RMI, DIS and ALSP simulation and application distribution frameworks can support distributed system interoperability, but in varying degrees. None of them can fully satisfy the requirement of the federated approach and especially as concerned with the component coupling, time management, ownership management, environment flexibility and data distribution services (Bruzzone et al, 2005;Buss and Jackson, 1998;IEEE, 1995;Weatherly et al, 1993).…”

Section: Existing Modelsmentioning

confidence: 99%

Enterprise operating system framework: federated interoperability based on HLA

Youssef

Zacharewicz

Chen

et al. 2018

IJSPM

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Operating system (OS) is a well-known concept in computer science as an interface between human and computer hardware (MacOS, Windows, IOS, Android). In the perspective of developing future generation of enterprise systems based on IoT and cyber-physical system principles, this paper proposes to develop an enterprise operating system (EOS) that will act as an interface between enterprise business managers and enterprise resources performing enterprise operations. The paper presents at first a set of requirements and functionalities of EOS. Then a survey on existing relevant works is given and mapped to the requirements. After that the existing models related to the federated enterprise interoperability are presented. The architectures of envisioned EOS and the federated interoperability are outlined. The last part draws some conclusions and gives future perspectives.

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“…It is worth mentioning that the DCAS, like many other simulation tools, such as those presented by Bruzzone et al, 28 Wang et al 29 and Jense et al, 30 uses HLA to leverage the advantages of distributed simulations. The DCAS uses the commonly used HLA-based simulation structure.…”

Section: The Distributed Cyber Attack Simulator Frameworkmentioning

confidence: 99%

“…Therefore, the only difference of DCAS compared to its related works from the parallel/distributed simulation point of view is the difference between the simulation components that are running in different federates. For example, in a supply-chain management simulation, 28 the federates may correspond to the components in a supply-chain while in the DCAS, components correspond to the network, attacker and defender entities in a security penetration process.…”

Section: The Distributed Cyber Attack Simulator Frameworkmentioning

confidence: 99%

A distributed simulation framework for modeling cyber attacks and the evaluation of security measures

Ashtiani

Azgomi

2014

SIMULATION

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The aim of this work is to propose a framework for the distributed simulation of cyber attacks based on high-level architecture (HLA), which is a commonly used standard for distributed simulations. The proposed framework and the corresponding simulator, which is called the distributed cyber attack simulator (abbreviated by DCAS), help administrators to model and evaluate the security measures of the networks. At the core of the DCAS is a simulation engine based on Portico, which is an open source HLA run-time infrastructure. The DCAS works in two modes: interactive and automated. Three types of simulation components (which are called federates in HLA terminology) are considered in the framework: the (1) network federate, (2) attacker federate and (3) defender federate. The simulator provides features for graphical design of the network models, animated traffic simulation, data collection, statistical analysis and different consoles for attacking and defending elements (e.g., intrusion detection systems, intrusion prevention systems). To increase the fidelity of the simulation outputs, real-world payloads are used by the DCAS. All the exploits information and the parameters of various network elements are automatically extracted from the open source vulnerability database. Also, the Snort rule-set is used as the signature database of the defending elements. The architecture and algorithms of the DCAS and the corresponding underlying simulation engine plus the security evaluation results of two illustrative examples are presented in this paper.

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Agent Directed HLA Simulation for Complex Supply Chain Modeling

Abstract: The authors outline a new modeling methodology designed to simulate a complex logistics network and to ensure interoperability through application of Intelligent Agent High-Level Architecture for distributed supply chain management.

Cited by 26 publications

References 5 publications

Steering supply chains from a complex systems perspective

Steering supply chains from a complex systems perspective

Enterprise operating system framework: federated interoperability based on HLA

A distributed simulation framework for modeling cyber attacks and the evaluation of security measures

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