Interdependent Networks Research Articles

Towards a new era in the governance of integrated activation: A systematic review of the literature on the governance of welfare benefits and employment‐related services in Europe (2010–21)

AbstractThis article presents the results of a systematic literature review of research articles (N = 72) to study the governance logic of integrated activation policies and the problems relating to reintegrating welfare benefits with services. The inductive study of the problems indicated in the literature demonstrates both the vertical and horizontal aspects of the governance of integrated activation at the street level: challenges are tied to the top‐down activation policy; requirements and strategies of delivering benefits and services; collaboration and coordination in delivery chains; and risks and inequality that streel‐level bureaucrats are trying to deal with in their work. The results point primarily to flaws in the vertical governance of activation, such as frontline work problems and collaborative practices between different actors and agencies. Moreover, some problems relating to collaboration and coordination, pointed towards the challenges in horizontal governance of activation. The article, however, demonstrates how the governance of integrated activation requires a coupling of these different streams of governance and understanding governance as a complex network of interdependencies and causal connections between institutions, organisations, and co‐production with end users.

Attack–Defense Game in Interdependent Networks: A Functional Perspective

Attack–Defense Game in Interdependent Networks: A Functional Perspective

Improving resilience of high-speed train by optimizing repair strategies

High-speed trains (HSTs) are used to transport passengers to destinations efficiently and safely. However, when HST units fail, strategies for repairing them are not available. Hence, to optimize repair strategies, an interdependent network is used to model an HST, and a metric of resilience based on network theory is introduced. Based on practical factors, an interdependent machine–electricity–communication network (IMECN) and related cascading failure models are developed. Comprehensive robustness metrics for the IMECN and nodes are proposed considering the topology of networks and functional features of nodes. Accordingly, a resilience optimization model of the IMECN subject to disturbances is formulated and solved using a tabu search (TS) algorithm. Finally, a real-world HST is considered to analyze the optimal repair strategy for different numbers of failed nodes. Analysis results show that the recovery process under the optimal repair strategy has at most three stages. When a few nodes and less than half of the nodes fail, the highest and lowest levels of the IMECN are achieved, respectively. Moreover, the characteristics of the preferentially repaired node in terms of importance, vulnerability, network type, and interdependency are analyzed. Results indicate that the optimal repair strategy is not necessarily determined by topological metrics.

Auctions for resource allocation and decentralized restoration of interdependent networks

Auctions for resource allocation and decentralized restoration of interdependent networks

Optimal defense strategy selection method for CPS considering integrated cyber–physical losses

Cyber-attacks against the cyber–physical power system (CPPS) may lead to major power outages and even system collapse in severe cases. In order to quantify the attack losses and select optimal strategies to defend against cyber-attacks, this paper proposes a computational model of integrated cyber–physical losses based on the theory of interdependent network. Based on the multiple coupling relationship between cyber system and physical network, the monitoring system is regarded as the cyber–physical interaction layer, and the information network operation constraint, physical system load reduction constraint, and monitoring equipment operation constraint are established respectively to analyze the impact on another network after a failed node appears in one layer of network, and proposed the cyber–physical integrated loss objective function. The offensive and defensive processes are abstracted into a two-player zero-sum game model, which evolves into a multi-stage game according to the changes in the system state during the game, and the integrated cyber–physical loss is used as the game gain of both the attacker and defender, and the Minimax-Q algorithm is introduced to solve for the optimal gain and select the optimal defense strategy. Finally, the IEEE 30 node cyber–physical system is used as a simulation example to verify whether the proposed loss calculation model can effectively quantify the losses caused by the attack on the information network and the power grid, and has practical guidance for the selection of the optimal defense strategy.

Beyond the institution versus home care dichotomy: Lessons from a feeding‐tube medical home

AbstractDecades of rights‐based advocacy for people with disabilities have transitioned long‐term care in the United States from institutional settings to home‐based care provided by interdependent care networks. This paper argues that policies and practices within these home‐based care systems unintentionally produce and often perpetuate unrecognized structural violence on the recipients of care and the caregivers. Understanding the caregivers' experiences through a case study of a Facebook feeding tube family support group exposes the geographic realities and ableist underpinnings of the home‐based care model that undergird this violence. Further, I illustrate the contradictions of “home is best” ideology by focusing on three interwoven themes: structural dependency on unpaid mother‐experts, spatio‐temporal erasure through decentralization, and invasive surveillance structures. This research attends to how home‐based care, as a practice and a place, reflects broader patriarchal, gendered, and neoliberal concepts of autonomy and individual rights as expressed through policies like “person‐centered” care and the medical home model. While this analysis has theoretical, methodological, and policy implications, more important is the contextualization of family experiences that sometimes impacts life and death.

Percolation behavior analysis of weighted edge-coupled interdependent networks

The robustness of interdependent networks has received extensive attention from the inter-disciplinary fields. In reality, many interdependent systems have interdependence relationships not only between nodes but also between edges. Different from previous studies focusing on edge-coupled interdependent networks without consideration on coupling strength, in this paper, a weighted edge-coupled interdependent network model with coupling strength is proposed. Then, the cascading failure propagation mechanism caused by attacking a small percentage of edges is studied. Based on the self-consistent probability theory, theoretical framework is established to provide the mathematical analysis of robustness of weighted edge-coupled interdependent networks under edge attacks. The current results can help to understand the vulnerability of interdependent networks and provide useful suggestions for the protection and optimization of complex networked systems.

Multivariate recovery coupling in interdependent networks with cascading failure.

Interdependent networks are susceptible to catastrophic consequences due to the interdependence between the interacting subnetworks, making an effective recovery measure particularly crucial. Empirical evidence indicates that repairing the failed network component requires resources typically supplied by all subnetworks, which imposes the multivariate dependence on the recovery measures. In this paper, we develop a multivariate recovery coupling model for interdependent networks based on percolation theory. Considering the coupling structure and the failure-recovery relationship, we propose three recovery strategies for different scenarios based on the local stability of nodes. We find that the supporting network plays a more important role in improving network resilience than the network where the repaired component is located. This is because the recovery strategy based on the local stability of the supporting nodes is more likely to obtain direct benefits. In addition, the results show that the average degree and the degree exponent of the networks have little effect on the superior performance of the proposed recovery strategies. We also find a percolation phase transition from first to second order, which is strongly related to the dependence coefficient. This indicates that the more the recovery capacity of a system depends on the system itself, the more likely it is to undergo an abrupt transition under the multivariate recovery coupling. This paper provides a general theoretical frame to address the multivariate recovery coupling, which will enable us to design more resilient networks against cascading failures.

Percolation phase transition in the heterogeneous multi-coupled interdependent network

In previous studies, complex system models have often been set up in an oversimplified manner and the failure mechanism for nodes affected by each other is not correspond to reality. Accordingly, we develop a new model of heterogeneous multi-coupled interdependent networks and analyze the change in the giant component of the network after the attack in conjunction with the load redistribution mechanism. We first analyze the cascading failure process of the network analytically by recursive methods, estimate the critical phase transition threshold and the size of the giant component of the remaining network after network percolation, and find that the threshold of the WS sub-network is positively related to the average degree, and the BA sub-network is related to the power exponent λ of the distribution. When λ is less than or equal to 2, there is always a giant component in the network. After λ is greater than 3.4788⋯, there is no giant component. When λ is between 2 to 3.4788⋯, we found that the threshold of the sub-network is more influenced by the proportion of attacks (p1 and p2), and when p1 is larger, the sub-networks interact with each other, resulting in a smaller threshold for the BA sub-network, while the threshold of the WS sub-network is smaller in other cases. Finally, the cross-sectional comparison illustrates that as λ increases to 3.4788⋯, the robustness of the BA sub-network increases, contrary to the findings for single-layer networks. Overall, the heterogeneous multi-coupled interdependent network is more robust, and the giant component is greatly affected by the low robust sub-network, but its existence is related to the stock of nodes.

Identification of novel clusters of co-expressing cytokines in a diagnostic cytokine multiplex test.

Cytokines are mediators of the immune system that are essential for the maintenance, development and resolution of immune responses. Beneficial immune responses depend on complex, interdependent networks of signaling and regulatory events in which individual cytokines influence the production and release of others. Since disruptions in these signaling networks are associated with a wide spectrum of diseases, cytokines have gained considerable interest as diagnostic, prognostic and precision therapy-relevant biomarkers. However, currently individual cytokines testing has limited value because the wider immune response context is often overlooked. The aim of this study was to identify specific cytokine signaling patterns associated with different diseases. Unbiased clustering analyses were performed on a clinical cytokine multiplex test using a cohort of human plasma specimens drawn from individuals with known or suspected diseases for which cytokine profiling was considered clinically indicated by the attending physician. Seven clusters of co-expressing cytokines were identified, representing common patterns of immune activation. Common expression profiles of the cytokine clusters and preliminary associations of these profiles with specific diseases or disease categories were also identified. These findings increase our understanding of the immune environments underlying the clinical presentations of patients of inflammatory, autoimmune and neoplastic diseases, which could then improve diagnoses and the identification of evidence-based treatment targets.

Evaluation of network expansion decisions for resilient interdependent critical infrastructures with different topologies

Resilient interdependent critical infrastructures (CIs) can better withstand cascading failures in disruptive events. This study proposes network expansion as a resilience improvement strategy for interdependent CIs and evaluates the influence of topology in interdependent network design for resilience optimization under disruption uncertainty. A resilience score consisting of network complexity and unmet demand metrics is introduced to quantify the resilience of expanded networks. Five synthetic interdependent network instances with random and hub-and-spoke (i.e., cluster) topologies are generated to represent CIs with heterogeneous node functions. Different network expansion opportunities are considered and critical node disruption scenarios are used to evaluate the impact of uncertain disruptions. We apply a two-stage stochastic multi-objective resilience optimization model to determine strategic investment decisions using the expected total cost and expected resilience score as competing objectives. Compromise solutions of expanded network designs are identified from Pareto optimal solutions and they are characterized according to their graph properties. The results show that expanded networks have improved resilience and the extent of improvement is affected by the network topology and type of disruption. Under critical node disruptions, a random network is more resilient than a hub-and-spoke structure due to its better connectivity. Characteristics of highly connected interdependent networks are high average node degree, high clustering coefficient, and low average shortest path length. Resilience improvement is more limited in expanded networks with a hub-and-spoke structure due to the negative impact of hub failures.

ResQ-IOS: An iterative optimization-based simulation framework for quantifying the resilience of interdependent critical infrastructure systems to natural hazards

Critical Infrastructure Systems are highly complex and interdependent. Growing complexity and interdependency between infrastructure systems and frequent exposure to extreme events have inevitably increased the probability of cascading failures and the prolonged lack of serviceability in urban communities, especially so for energy systems. The resilience analysis of interdependent infrastructure systems against natural hazards provides stakeholders with a comprehensive outlook on recovery strategies to minimize the damage costs and losses caused by extreme events. This paper introduces the ResQ-IOS, a Resilience Quantification Iterative Optimization-based Simulation (IOS) framework for quantifying the resilience of interdependent infrastructure systems to natural hazards with the capability of considering the real-world conditions for the status of infrastructure systems' components. The ResQ-IOS framework consists of five modules: risk assessment, simulation, optimization, database, and controller. To evaluate the capabilities of this framework, the seismic resilience of interdependent energy infrastructure networks (power, natural gas, and water) in Shelby County (TN), USA, was assessed. The results of the resilience analysis of the case study suggest that the water network is the best candidate for implementing pre-disaster Resilience Enhancement Measures (REMs), like increasing the supply capacity. Due to the controlling role of the power network in the community's recovery process, it is recommended that post-disaster REMs, such as increasing the number of Repair and Maintenance (R&M) teams, should be applied to the power network to speed up the restoration of failed components in that network and consequently, shorten the recovery duration of the community. The ResQ-IOS can be employed as a useful computational tool for planning the resilience-oriented sustainable development of urban communities by, for example, deploying Renewable Energy (RE)-based strategies to enhance their disaster resilience.

Understanding digital services in GVCs: An extended gravity model through the lens of network analysis

AbstractCountries are increasingly incorporating foreign digital services in their exports, creating new and complex interdependencies between economies, which suggests a new channel for the expansion of global value chains (GVCs). To better understand how these new and complex interdependencies are evolving, we apply a novel methodological framework. First, using social network analysis methodology, we calculate several indicators that capture these complex network interdependencies. Second, we include these indicators in the second stage of a two‐step gravity model that explains (in the first step) dyadic trade flows of embodied digital services. Our motivation for this two‐stage approach is to avoid difficulties that traditional gravity models have in incorporating complex network interdependencies. Our empirical results suggest statistically significant effects of such interdependencies in the embodied digital services trade flows.

Assessing edge-coupled interdependent network disintegration via rank aggregation and elite enumeration

The disintegration of networks is a widely researched topic with significant applications in fields such as counter-terrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks (RAEEC), which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges. We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.

Manufacturers’ Acquiescence to Buyers’ Sourcing Requests in Industrial Markets

ABSTRACT Purpose This study examines a three-level interdependent hierarchical supply chain and explores the antecedents and consequences of a manufacturer’s acquiescence to a buyer’s request to source a component from a designated component supplier. Methodology This research collected survey data from 212 Chinese mining companies and analyzed the data using structural equation models. Findings First, a manufacturer’s acquiescence is negatively associated with its industrial knowledge and technological capability as perceived by the buyer, but positively correlated with the relational ties between the buyer and the designated component supplier. Second, the detailing efforts strengthen the impact of perceived industrial knowledge but weaken that of relational ties on acquiescence. Third, the manufacturer’s acquiescence ensures the buyer’s power maintenance and procurement outcome certainty, and improves the manufacturer’s customer loyalty and control of sourcing information. Research implications The research highlights the significance of understanding acquiescence within an interdependent supply chain network and indicates that acquiescence will not necessarily lead to the acquiescing firm’s dependence disadvantage. Practical implications The research suggests that firms can use acquiescence to preserve interdependent supply chain relationships. When deciding whether to acquiesce or not, firms should consider not only the market perceptions of their resources and capabilities but also the supply chain networks. Detailing can be an effective method to reduce the pressure for acquiescence. Originality In the context of a manufacturer’s sourcing decisions, the research provides fresh insights into acquiescence in a three-level hierarchical supply chain relationship.

Robustness of interdependent higher-order networks

In real complex systems, interactions occur not only between a pair of nodes, but also in groups of three or more nodes, which can be abstracted as higher-order structures in the networks. The simplicial complex is one of a model to represent systems with both low-order and higher-order structures. In this paper, we study the robustness of interdependent simplicial complexes under random attacks, where the complementary effects of the higher-order structure are introduced. When a higher-order node in a 2-simplex fails, its dependent node in the other layer survives with a certain probability due to the complementary effects from the 2-simplex. By using the percolation method, we derive the percolation threshold and the size of the giant component when the cascading failure reaches its steady state. The simulation results agree well with analytical predictions. We find that the type of phase transition changes from the first-order to the second-order when the complementary effect of the higher-order structure on the dependent node increases or the number of 2-simplices in the interdependent simplicial complex increases. While the interlayer coupling strength increases, the type of phase transition changes from the second-order to the first-order. In particular, even if the higher-order interactions do not provide complementary effects for dependent nodes, the robustness of the interdependent heterogeneous simplicial complex is higher than that of the ordinary interdependent network with the same average degree due to the existence of 2-simplices in the system. This study furthers our understanding in the robustness of interdependent higher-order networks.

Robustness of Interdependent Power Grid and Communication Networks to Cascading Failures

We consider the cascading failure process in interdependent power-communication networks, where the power grid provides the required energy for the communication nodes, and the communication network facilitates the monitoring and controlling the power networks. The proposed system model considers the flow dynamics in both networks and the failure rollover to study the cascade process in the system and capture the possible beneficial and adverse effects of interdependency between the networks. We suggest weak and strong interdependencies models that determine how and to what extent the loss of controllability after failures impacts the power network and a congestion-aware load balancing scheme that exploits the system state to decrease the density of severe cascades. The results of the cascading failure processes on data from two power networks are provided and discussed in terms of the average unserved load in the power network and the number of failed nodes in the communication layer in different scenarios. We find that increasing the coupling is beneficial in most cases; however, considering the robustness of each network and the nature of the interdependencies between the two networks, over-coupling can decrease the system's robustness against failure cascading in certain scenarios.

Collective Resilience: Deterring China's Weaponization of Economic Interdependence

Abstract Since the 2010s, China has used economic coercion against Western and Asian states to achieve territorial and political goals. China's leveraging of its market is a form of “predatory liberalism” that weaponizes the networks of interdependence created by globalization. The United States and other like-minded partners have mostly used piecemeal “de-risking” measures such as decoupling, supply chain resilience, reshoring, and trade diversion to reduce dependence on China and thereby minimize vulnerability to its economic coercion. But these practices do not stop the Chinese government's economic bullying. “Collective resilience” is a peer competition strategy designed to deter the Xi Jinping regime's economic predation. What informs this strategy is the understanding that interdependence, even asymmetric interdependence, is a two-way street. Original trade data show that the previous and current targets of economic coercion by the Xi Jinping regime export over $46.6 billion worth of goods to China on which it is more than 70 percent dependent as a proportion of its total imports of those goods. These target states could band together in a collective resilience alliance and practice economic deterrence by promising to retaliate against China's high-dependence trade should Beijing act against any one of the alliance members.

MARGINÀLIA, Interdependent Design Processes and the Ethics of Care.

In this article we present MARGINALIA, an academic experience of design carried out within the context of the Final Bachelor of Design Projects of the Visual Creation mention. MARGINALIA is a collaborative workshop that aim to be a tool for amplifying the first drafts of the Final Design Project. It’s a process-oriented design approach, exploratory and experimental. The designers intrude (interfere, involve, intermediate) in the project of the others, developing and extending it towards territories that the author could barely imagine. Applying the ethics of care to the project of design we explore new paths to reinvent the design project and move it from a personal outcome to an interdependent result. We argue that design practices have the capacity to foster cooperation, empathy and shared creation through the vision of ethics of care. We embrace the point of view of the design of care and we transform the design project into a relational infrastructure and a network of interdependencies. With MARGINALIA we inseminate a way of projecting forgetting the traditional design project, which privilege abstract principles, formal rules, impersonal duties and deliberative justice. And we promote a new paradigm where design project is relational.

Cooperation dynamics of the population with interactive diversity on interdependent networks

The population is often massive, and interacting patterns among individuals is also teeming with diversity and uncertainty. In order to explore the role of interactive diversity in the evolution of cooperation, we introduce two different types of agents into the game system: one is the node-strategy agent who will adopt the same interactive strategy for all neighbors; the other one is the link-strategy agent who will apply different strategies when confronting different neighbors. At the same time, we also investigate the impact of the coupling of multi-layer networks on large-scale group cooperation. The inter-layer coupling factors can achieve the purpose of information sharing to a certain extent through unrelated groups, thereby affecting the final cooperation. Monte Carlo simulation results show that under suitable social dilemmas, when the whole population plays the prisoner’s dilemma game, the diversity of individual interactive is conducive to improving the overall cooperation level, and the coupling between networks also has a positive impact on the emergence of cooperation. By contrast, the diversity of individual interaction and the coupling between networks will reduce the cooperation level when the population plays the snowdrift game. Current results are immensively conducive to understanding the universal cooperation phenomena inside many real-world networked systems.