Estimating node connectedness in spatial network under stochastic link disconnection based on efficient sampling

Fushimi, Takayasu; Saito, Kazumi; Ikeda, Tetsuo; Kazama, Kazuhiro

doi:10.1007/s41109-019-0187-3

Cited by 7 publications

(5 citation statements)

References 31 publications

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“…Landmark nodes are special nodes in the network, typically aiding to speed up internal computations such as centrality measures. This is of interest in case of dealing with large-scale networks or with near real-time operations [179,180]. For instance, in the work of Giudicciani et al [181] landmark nodes are selected as nodes in the boundary of network communities (nodes with links connecting nodes of other community).…”

Section: Complex Network For Control and Optimisationmentioning

confidence: 99%

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

et al. 2020

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Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.Processes 2020, 8, 312 2 of 29 in a telecommunication system network, nodes (e.g., routers and switches) may suffer over time a degradation in their properties that may lead them to diminish their performance. However, just the daily variation on traffic demand also has an impact on such nodes performance. Unexpected, external intervention such as cyber-attacks or extreme weather conditions may affect the properties, even the topology of a telecommunication system.Intelligent distributed systems are capable of modelling how different parts of the network might work individually and collectively [10]. Ultimately, this is used as support for any decision-making system aiming to achieve better overall system functioning and its consequent performance. Intelligent distributed systems encompass autonomous learning units that can be associated with the nodes of a complex network. These intelligent network nodes are able to act independently and also interact with other nodes to pursue both individual (local) and general system-level targets. The necessary communication between individuals can be represented by links of the complex network connecting their nodes. It is natural to understand such nodes as intelligent agents within a MAS framework. Each agent separately obeying simple rules but working together with other agents makes it possible to approach complex engineering challenges. Intelligent distributed systems have been proposed in a broad range of engineered complex systems [11,12]. Precisely, the review proposed herein focuses only on engineered systems and manufacturing processes, given the wide spectrum of the approached topic. Out of this review fall, then, topics related to social systems analysis such as migration models [13,14] or online social media [15,16]. Similarly, natural systems are out of this review scope. This is the case of computational chemistry [17,18], biology [19,20], and metabolic networks [21,22].Automatic optimisation and control in an engineering system is associated with a near real-time data acquisition and an optimal decision-making. Th...

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Section: Complex Network For Control and Optimisationmentioning

confidence: 99%

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

et al. 2020

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“…Landmark nodes are special nodes in the network, typically aiding to speed up internal computations such as centrality measures. This is of interest in case of dealing with large-scale networks or with near real-time operations [170,171]. For instance, in the work of Giudicciani et al [172] landmark nodes are selected as nodes in the boundary of network communities (nodes with links connecting nodes of other community).…”

Section: Complex Network For Control and Optimisationmentioning

confidence: 99%

A Review on Control and Optimisation of Multi-Agent Systems and Complex Networks for Systems Engineering

Herrera¹,

Hernández²,

Parlikad³

et al. 2020

Preprint

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Systems Engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address Systems Engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in Industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks; along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant.

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“…Human behavior is a critical factor in how these interactions enable pathogens to disseminate, evolve, and manifest as infectious diseases [5] (pp. [3][4][5][6][7][8][9][10][11][12][13][14]. Therefore, collective and coordinated actions are required to manage public bad risks (risk governance) like infectious diseases.…”

Section: Introductionmentioning

confidence: 99%

“…Third, we explored the use of spatial analytical methods to understand the dynamic relationship between the multiple related socio-ecological factors, decision making, and resilience. To do so, we developed a computational program that includes both decisional and spatial dimensions to assist with analyzing the game's results (inspired by principles of neighbors, connectedness, and centrality analysis [13,14].…”

Section: Introductionmentioning

confidence: 99%

A Public Bad Game Method to Study Dynamics in Socio-Ecological Systems (Part II): Results of Testing Musa-Game in Rwanda and Adding Emergence and Spatiality to the Analysis

et al. 2021

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This article is the second in a series of two and presented findings from field-testing an experimental boardgame (Musa-game) with banana farmers in four villages in Eastern Rwanda. The conceptualization and design of the Musa-game were described in Part I. Musa-game gives insights into how farmers’ individual and collective decision-making and actions regarding management of a public bad interplay with other factors and characteristics of the socio-ecological system (SES). A public bad is a non-rivalrous, non-excludable issue that causes loss of social-welfare of individuals and communities. The method contributes contextual understanding about the emergence of phenomena that arise from the interactions between human and non-human actors. Musa-game was framed to study one public bad challenge in particular: the infectious crop disease Banana Xanthomonas Wilt disease (BXW). Findings increased the knowhow about the emergence and governance of conditions that hinder or enhance the spread of infectious diseases like BXW. Analysis of qualitative and quantitative data suggested that individual farmers’ actions were influenced by perceptions of risk, affecting both individual and collective disease management. Additionally, the used experimental treatments allowed us to evaluate the influence of communication on risk-governance strategies. It appears that a combination of possession of technical knowledge about the disease, opportunities to communicate about the disease, and a collective disease management strategy enables the best individual actions and collective performance.

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Estimating node connectedness in spatial network under stochastic link disconnection based on efficient sampling

Cited by 7 publications

References 31 publications

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

A Review on Control and Optimisation of Multi-Agent Systems and Complex Networks for Systems Engineering

A Public Bad Game Method to Study Dynamics in Socio-Ecological Systems (Part II): Results of Testing Musa-Game in Rwanda and Adding Emergence and Spatiality to the Analysis

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