Robustness of interrelated traffic networks to cascading failures

The vulnerability to real-life networks against small initial attacks has been one of outstanding challenges in the study of interrelated networks. We study cascading failures in two interrelated networks S and B composed from dependency chains and connectivity links respectively. This work proposes a realistic model for cascading failures based on the redistribution of traffic flow. We study the Barabási-Albert networks (BA) and Erd's-Rényi graphs (ER) with such structure, and found that the efficiency sharply decreases with increasing percentages of the dependency nodes for removing a node randomly. Furthermore, we study the robustness of interrelated traffic networks, especially the subway and bus network in Beijing. By analyzing different attacking strategies, we uncover that the efficiency of the city traffic system has a non-equilibrium phase transition at low capacity of the networks. This explains why the pressure of the traffic overload is relaxed by singly increasing the number of small buses during rush hours. We also found that the increment of some buses may release traffic jam caused by removing a node of the bus network randomly if the damage is limited. However, the efficiencies to transfer people flow will sharper increase when the capacity of the subway network αS > α0

A survey on multilayer networks modelled to assess robustness in infrastructure systems

The development of modern societies places particular demands on the consistent performance of infrastructure systems. Because multilayer network models are capable of representing the interdependencies between infrastructure components, they have been widely used to analyse the robustness of infrastructure systems. This present study is a systematic review of literature, published since 2010. It aims to investigate how multilayer network models have been used in analysing the robustness of infrastructure systems. According to findings, percolation theory was the most popular method used in about 57% of papers. Regarding the properties, coupling strength and node degree were the most common while directed links and feedback conditions were the least common. The following gaps were identified which provide opportunities for further research. These include the absence of models based on real-world data and the need for models that make fewer simplifying assumptions about complex systems. No papers considered all potential properties, and their effect on boosting or weakening each other’s effect. By considering all properties, the importance of different properties on the robustness of infrastructure systems can be quantified and compared in future studies

Network Properties for Robust Multilayer Infrastructure Systems: A Percolation Theory Review

Infrastructure systems, such as power, transportation, telecommunication, and water systems, are composed of multiple components which are interconnected and interdependent to produce and distribute essential goods and services. So, the robustness of infrastructure systems to resist disturbances is crucial for the durable performance of modern societies. Multilayer networks have been used to model the multiplicity and interrelation of infrastructure systems and percolation theory is the most common approach to quantify the robustness of such networks. This survey systematically reviews literature published between 2010 and 2021, on applying percolation theory to assess the robustness of infrastructure systems modeled as multilayer networks. We discussed all network properties applied to build infrastructure models. Among all properties, interdependency strength and communities were the most common network property whilst very few studies considered realistic attributes of infrastructure systems such as directed links and feedback conditions. The review highlights that the properties produced approximately similar model outcomes, in terms of detecting improvement or deterioration in the robustness of multilayer infrastructure networks, with few exceptions. Most of the studies focused on highly simplified synthetic models rather than models built by real datasets. Thus, this review suggests analyzing multiple properties in a single model to assess whether they boost or weaken the impact of each other. In addition, the effect size of different properties on the robustness of infrastructure systems should be quantified. It can support the design and planning of robust infrastructure systems by arranging and prioritizing the most effective properties

Network Properties for Robust Multilayer Infrastructure Systems: A Percolation Theory Review

Infrastructure systems, such as power, transportation, telecommunication, and water systems, are composed of multiple components which are interconnected and interdependent to produce and distribute essential goods and services. So, the robustness of infrastructure systems to resist disturbances is crucial for the durable performance of modern societies. Multilayer networks have been used to model the multiplicity and interrelation of infrastructure systems and percolation theory is the most common approach to quantify the robustness of such networks. This survey systematically reviews literature published between 2010 and 2021, on applying percolation theory to assess the robustness of infrastructure systems modeled as multilayer networks. We discussed all network properties applied to build infrastructure models. Among all properties, interdependency strength and communities were the most common network property whilst very few studies considered realistic attributes of infrastructure systems such as directed links and feedback conditions. The review highlights that the properties produced approximately similar model outcomes, in terms of detecting improvement or deterioration in the robustness of multilayer infrastructure networks, with few exceptions. Most of the studies focused on highly simplified synthetic models rather than models built by real datasets. Thus, this review suggests analyzing multiple properties in a single model to assess whether they boost or weaken the impact of each other. In addition, the effect size of different properties on the robustness of infrastructure systems should be quantified. It can support the design and planning of robust infrastructure systems by arranging and prioritizing the most effective properties

Cascading Failures in Complex Networks

Cascading failure is a potentially devastating process that spreads on real-world complex networks and can impact the integrity of wide-ranging infrastructures, natural systems, and societal cohesiveness. One of the essential features that create complex network vulnerability to failure propagation is the dependency among their components, exposing entire systems to significant risks from destabilizing hazards such as human attacks, natural disasters or internal breakdowns. Developing realistic models for cascading failures as well as strategies to halt and mitigate the failure propagation can point to new approaches to restoring and strengthening real-world networks. In this review, we summarize recent progress on models developed based on physics and complex network science to understand the mechanisms, dynamics and overall impact of cascading failures. We present models for cascading failures in single networks and interdependent networks and explain how different dynamic propagation mechanisms can lead to an abrupt collapse and a rich dynamic behavior. Finally, we close the review with novel emerging strategies for containing cascades of failures and discuss open questions that remain to be addressed.Comment: This review has been accepted for publication in the Journal of Complex Networks Published by Oxford University Pres

Towards real-world complexity: an introduction to multiplex networks

Many real-world complex systems are best modeled by multiplex networks of interacting network layers. The multiplex network study is one of the newest and hottest themes in the statistical physics of complex networks. Pioneering studies have proven that the multiplexity has broad impact on the system's structure and function. In this Colloquium paper, we present an organized review of the growing body of current literature on multiplex networks by categorizing existing studies broadly according to the type of layer coupling in the problem. Major recent advances in the field are surveyed and some outstanding open challenges and future perspectives will be proposed.Comment: 20 pages, 10 figure

Robustness of double-layer group-dependent combat network with cascading failure

The networked combat system-of-system (CSOS) is the trend of combat development with the innovation of technology. The achievement of combat effectiveness requires CSOS to have a good ability to deal with external interference. Here we report a modeling method of CSOS from the perspective of complex networks and explore the robustness of the combat network based on this. Firstly, a more realistic double-layer heterogeneous dependent combat network model is established. Then, the conditional group dependency situation is considered to design failure rules for dependent failure, and the coupling relation between the double-layer subnets is analyzed for cascading failure. Based on this, the initial load and capacity of the node are defined, respectively, as well as the load redistribution strategy and the status judgment rules for the cascading failure model. Simulation experiments are carried out by changing the attack modes and different parameters, and the results show that the robustness of the combat network can be effectively improved by improving the tolerance limit of one-way dependency of the functional net, the node capacity of the functional subnet and the tolerance of the overload state. The conclusions of this paper can provide a useful reference for network structure optimization and network security protection in the military field

Enhancing network robustness using software-defined networking

Doctor of PhilosophyDepartment of Electrical and Computer EngineeringDon M. GruenbacherCaterina M. ScoglioAs today's networks are no longer individual networks, networks are less robust towards failures and attacks. For example, computer networks and power networks are interdependent. Computer networks provide smart control for power networks, while power networks provide power supply. Localized network failures and attacks are amplified and exacerbated back and forth between two networks due to their interdependencies. This dissertation focuses on finding solutions to enhance network robustness. Software-defined networking provides a programmable architecture, which can dynamically adapt to any changes and can reduce the complexities of network traffic management. This architecture brings opportunities to enhance network robustness, for example, adapting to network changes, routing traffic bypassing malfunction devices, dropping malicious flows, etc. However, as SDN is rapidly proceeding from vision to reality, the SDN architecture itself might be exposed to some robustness threats. Especially, the SDN control plane is tremendously attractive to attackers, since it is the "brain" of entire networks. Thus, researching on network robustness helps protect network from a destructive disaster. In this dissertation, we first build a novel, realistic interdependent network framework to model cyber-physical networks. We allocate dependency links under a limited budget and evaluate network robustness. We further revise a network flow algorithm and find solutions to obtain a basic robust network structure. Extensive simulations on random networks and real networks show that our deployment method produces topologies that are more robust than the ones obtained by other deployment techniques. Second, we tackle middlebox chain problems using SDN. In computer networks, applications require traffic to sequence through multiple types of middleboxes to accomplish network functionality. Middlebox policies, numerous applications' requirements, and resource allocations complicate network management. Furthermore, middlebox failures can affect network robustness. We formulate a mixed-integer linear programming problem to achieve a network load-balancing objective in the context of middlebox policy chain routing. Our global routing approach manages network resources efficiently by simplifying candidate-path selections, balancing the entire network and using the simulated annealing algorithm. Moreover, in case of middlebox failures, we design a fast rerouting mechanism by exploiting the remaining link and middlebox resources locally. We implement proposed routing approaches on a Mininet testbed and evaluate experiments' scalability, assessing the effectiveness of the approaches. Third, we build an adversary model to describe in detail how to launch distributed denial of service (DDoS) attacks to overwhelm the SDN controller. Then we discuss possible defense mechanisms to protect the controller from DDoS attacks. We implement a successful DDoS attack and our defense mechanism on the Mininet testbed to demonstrate its feasibility in the real world. In summary, we vertically dive into enhancing network robustness by constructing a topological framework, making routing decisions, and protecting the SDN controller

Network robustness improvement via long-range links

Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies