Resilience and survivability in communication networks: Strategies,principles, and survey of disciplines

The Internet has become essential to all aspects of modern life, and thus the consequences of network disruption have become increasingly severe. It is widely recognised that the Internet is not sufficiently resilient, survivable, and dependable, and that significant research, development, and engineering is necessary to improve the situation. This paper provides an architectural framework for resilience and survivability in communication networks and provides a survey of the disciplines that resilience encompasses, along with significant past failures of the network infrastructure. A resilience strategy is presented to defend against, detect, and remediate challenges, a set of principles for designing resilient networks is presented, and techniques are described to analyse network resilience.     

Challenges for the cyber-physical manufacturing enterprises of the future

This paper summarizes a vision of the challenges facing the so-called “Industry of the Future” as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.     

A general framework for assessing system resilience using Bayesian networks: A case study of sulfuric acid manufacturer

Supply chains play an important role in modern society and national economic development. In recent years, supply chains are more susceptible to variety of disruptive events, including natural disasters, man-made attacks, and common failures due to their complexity, globalization, and interconnected structures. Hence, it is important to design resilient supply chains which are capable of withstanding and recovering rapidly from disruptive events. This paper first explores the key drivers that contribute to the design of resilient supply chains based on the notion of absorptive, adaptive and restorative capacities. Second, it introduces a generic conceptual framework comprising five key phases: threat analysis, resilience capacity design, resilience cost evaluation, resilience quantification, and resilience improvement. The primary challenge to the literature of system resilience is how to measure it qualitatively. Findings from literature indicate that many of the drivers to the system resilience are qualitative such as staff cooperation and collaboration during disruptive events, level of preparation against natural disaster, among others. To fill the gap between qualitative and quantitative assessment of resilience, we employed Bayesian network to quantify the system resilience. Bayesian network is a rigorous tool for measuring risks under uncertainty, representing dependency between causes and effects, and making special types of reasoning. Additionally, it is capable of handling both qualitative and quantitative variables in terms of probability. We implemented Bayesian network for quantifying the supply chain system resilience of sulfuric acid manufacturer in Iran. Different scenarios have been defined and implemented to identify critical variables that are susceptible to the system resilience of sulfuric acid manufacturer.     

Minimal fault diameter for highly resilient product networks

We present a number of results related to the fault tolerance of Cartesian product networks. We start by presenting a method for building containers (i.e., sets of node-disjoint paths) between any two nodes of a product network based on given containers for the factor networks. Then, we show that the best achievable fault diameter (i.e., diameter under maximum fault conditions), under reasonable network regularity and connectivity conditions, is equal to the fault-free diameter plus one. The concept of high fault resilience is then defined. We then prove that if each factor network is highly resilient, then their Cartesian product has minimal fault diameter. We derive from these results that Cartesian products of several popular networks are highly resilient and have minimal fault diameter equal to diameter plus one. These results spare future efforts that would be needed to individually determine the fault diameter of such networks as has been the practice with previously studied networks.     

A sinkhole resilient protocol for wireless sensor networks: Performance and security analysis

This work focuses on: (1) understanding the impact of selective forwarding attacks on tree-based routing topologies in wireless sensor networks (WSNs), and (2) investigating cryptography-based strategies to limit network degradation caused by sinkhole attacks. The main motivation of our research stems from the following observations. First, WSN protocols that construct a fixed routing topology may be significantly affected by malicious attacks. Second, considering networks deployed in a difficult to access geographical region, building up resilience against such attacks rather than detection is expected to be more beneficial. We thus first provide a simulation study on the impact of malicious attacks based on a diverse set of parameters, such as the network scale and the position and number of malicious nodes. Based on this study, we propose a single but very representative metric for describing this impact. Second, we present the novel design and evaluation of two simple and resilient topology-based reconfiguration protocols that broadcast cryptographic values. The results of our simulation study together with a detailed analysis of the cryptographic overhead (communication, memory, and computational costs) show that our reconfiguration protocols are practical and effective in improving resilience against sinkhole attacks, even in the presence of collusion.     

A Formal Model of Crash Recovery in a Distributed System

A formal model for atomic commit protocols for a distributed database system is introduced. The model is used to prove existence results about resilient protocols for site failures that do not partition the network and then for partitioned networks. For site failures, a pessimistic recovery technique, called independent recovery, is introduced and the class of failures for which resilient protocols exist is identified. For partitioned networks, two cases are studied: the pessimistic case in which messages are lost, and the optimistic case in which no messages are lost. In all cases, fundamental limitations on the resiliency of protocols are derived.     

Water Supply Networks as Cyber-physical Systems and Controllability Analysis

Cyber-physical systems (CPS) is a system of systems which consists of many subsystems that can stand alone in an individual manner and can be taken as a typical complex network. CPS can be applied in the critical infrastructures such as water supply networks, energy supply systems, and so on. In this paper, we analyze the structure of modern city water supply networks from the view of CPS theory. we use complex network theory to build an undirected and unweighted complex network model for the water supply networks to investigate the structural properties, and present the structure of the water supply networks and detect communities by a spectral analysis of the Laplacian matrix. Then, we analyze the structure and controllability of water supply networks by the structural controllability method. The results show the feasibility and effectiveness of the proposed complex network model.      

Understanding activated network resilience: A comparative analysis of co‐located and co‐cluster disaster response networks

Building on the resilience literature, this study analyzes the response networks that were activated for four disasters during 2015–2016 (Cyclone Pam, the 2015 Nepal earthquake, Cyclone Winston, the 2016 Ecuador earthquake). The analysis shows that different interrelated resilient capacities are manifested in the activation of response networks. In particular, in exhibiting redundancy and robustness, disaster‐specific network structures are discerned. In both cyclones, response networks resemble a predefined cluster design, whereas in the earthquake disasters, networks are more fluid. Moreover, organizations' varied levels of prior response experiences help build the network's capacities of redundancy and resourcefulness. Implications are discussed in ways to advance contributions to research on resilience and disaster response networks.     

基于应急供应的弹性供应网络设计研究

在传统供应网络和多源供应网络设计的基础上,结合战略应急库存和实物期权两种应急供应方法,建立了基于应急供应的弹性供应网络模型,并进行了算例验证．研究结果表明,与传统的供应网络模型相比,该模型更具有现实意义,不但能显著提高供应网络的弹性,而且能达到网络成本、可靠性和弹性三者之间的平衡．     

An agent-based approach for e-manufacturing and supply chain integration

A major problem facing manufacturing organisations is how to provide efficient and cost-effective responses to the unpredictable changes taking place in a global market. This problem is made difficult by the complexity of supply chain networks coupled with the complexity of individual manufacturing systems within supply chains. Current systems such as manufacturing execution systems (MES), supply chain management (SCM) systems and enterprise resource planning (ERP) systems do not provide adequate facilities for addressing this problem. This paper presents an approach that would enable manufacturing organisations to dynamically and cost-effectively integrate, optimise, configure, simulate, restructure and control not only their own manufacturing systems but also their supply networks, in a co-ordinated manner to cope with the dynamic changes occurring in a global market. This is realised by a synergy of two emerging manufacturing concepts: Agent-based agile manufacturing systems and e-manufacturing. The concept is to represent a complex manufacturing system and its supply network with an agent-based modelling and simulation architecture and to dynamically generate alternative scenarios with respect to planning, scheduling, configuration and restructure of both the manufacturing system and its supply network based on the coordinated interactions amongst agents.     

On system state equipartitioning and semistability in network dynamical systems with arbitrary time-delays

In many applications involving multiagent systems, groups of agents are required to agree on certain quantities of interest. In particular, it is important to develop consensus protocols for networks of dynamic agents with directed information flow, switching network topologies, and possible system time-delays. In this paper, we use compartmental dynamical system models to characterize dynamic algorithms for linear and nonlinear networks of dynamic agents in the presence of inter-agent communication delays that possess a continuum of semistable equilibria, that is, protocol algorithms that guarantee convergence to Lyapunov stable equilibria. In addition, we show that the steady-state distribution of the dynamic network is uniform, leading to system state equipartitioning or consensus. These results extend the results in the literature on consensus protocols for linear balanced networks to linear and nonlinear unbalanced networks with time-delays.     

Self-organizing and adaptive peer-to-peer network.

In this paper, an algorithm that forms a dynamic and self-organizing network is demonstrated. The hypothesis of this work is that in order to achieve a resilient and adaptive peer-to-peer (P2P) network, each network node must proactively maintain a minimum number of edges. Specifically, low-level communication protocols are not sufficient by themselves to achieve high-service availability, especially in the case of ad hoc or dynamic networks with a high degree of node addition and deletion. The concept has been evaluated within a P2P agent application in which each agent has a goal to maintain a preferred number of connections to a number of service providing agents. Using this algorithm, the agents update a weight value associated with each connection, based on the perceived utility of the connection to the corresponding agent. This utility function can be a combination of several node or edge parameters, such as degree k of the target node, or frequency of the message response from the node. This weight is updated using a set of Hebbian-style learning rules, such that the network as a whole exhibits adaptive self-organizing behavior. The principal result is the finding that by limiting the connection neighborhood within the overlay topology, the resulting P2P network can be made highly resilient to targeted attacks on high-degree nodes, while maintaining search efficiency.     

Topological analysis of a two coupled evolving networks model for business systems

In multi-agent systems, the underlying networks are always dynamic and network topologies are always changing over time. Performance analyses of topologies are important for understanding the robustness of the system and also the effects of topology on the system efficiency and effectiveness. In this paper, we present an example of a real-world distributed agent system, a digital business ecosystem (DBE). It is modelled as a two coupled network system. The upper layer is the business network layer where business process between different business agents happen. The lower layer is the underlying P2P communication layer to support communications between the agents. Algorithms for multi-agent tasks negotiation and execution, interaction between agents and the underlying communication network, evolutionary network topology dynamics, are provided. These algorithms consider the two network layers evolving over time, with effects on each other. Through a comprehensive set of discrete event simulation, we investigate the effects of different evolutionary principles inspired by random graph and scale-free network in complex network theory on the topological properties and performance of the underlying network. We also find several rules to design a resilient and efficient P2P network.     

An agent-based distributed computational experiment framework for virtual supply chain network development

This paper focuses on research on virtual supply chain networks instead of real supply chain networks by making use of agent technology and computational experiment method. However, the recent research is inefficient in computational experiment modeling and lack of a related methodological framework. This paper proposes an agent-based distributed computational experiment framework with in-depth study of material flow, information flow and time flow modeling in supply chain networks. In this framework, a matrix-based formal representation method for material flow, a task-centered representation method for information flow and an agent-based time synchronization mechanism for time flow are proposed to aid building a high quality computational experiment model for a multi-layer supply chain network. In order to conduct the model, a computational experiment architecture for virtual supply chain networks is proposed. In this architecture, coordination mechanisms among agents based on material flow, information flow and time flow as well as consistency check methods for computational experiment models are discussed. Finally, an implementation architecture of the framework is given and a case of virtual supply chain network is developed to illustrate the application of the framework. The computational experiment results of the case show that the proposed framework, not only feasible but correct, has sound advantages in virtual supply chain network development, computational experiment modeling and implementation.     

Stochastic network Price identity

Through the introduction of stochastic operators, the following work is an extension of previous works on robustness and resilience of compartmentalized closed-loop input-output systems. Indeed, those can be subject to the onset of external random perturbations which compromise the functioning of the input-output processing. The stochastic version of the network Price identity shows that the amplified expected dismantlement of the network structure comes from an increased expectation of external disturbers. Nevertheless, resilience can lead to a partial or full offset of threats. Furthermore, by studying the eigenvalues of the Laplacian, we provide a quantified value of connectivity to the between-subnetwork coupling. The value turns out to be greater in resilient networked structures than in the robust ones.     

Distributed robust finite-time nonlinear consensus protocols for multi-agent systems

This paper investigates the robust finite-time consensus problem of multi-agent systems in networks with undirected topology. Global nonlinear consensus protocols augmented with a variable structure are constructed with the aid of Lyapunov functions for each single-integrator agent dynamics in the presence of external disturbances. In particular, it is shown that the finite settling time of the proposed general framework for robust consensus design is upper bounded for any initial condition. This makes it possible for network consensus problems to design and estimate the convergence time offline for a multi-agent team with a given undirected information flow. Finally, simulation results are presented to demonstrate the performance and effectiveness of our finite-time protocols.     

Enhanced reliable reactive routing (ER3) protocol for multimedia applications in 3D wireless sensor networks

Sensor networks designed especially for the multimedia applications require high data rate and better Quality of Service (QoS). Offering a reliable and energy efficient routing technique in a harsh and complex three-dimensional (3-D) environment for multimedia applications is a challenging job. Geo-routing and geometric routing have been efficient routing schemes for two-dimensional (2-D), but are unable to work properly for 3-D sensor networks. In order to enhance the resilience to link the dynamics in the 3-D sensor network, in this research an Enhanced Reliable Reactive Routing (ER3) is proposed. ER3 is an advancement to the existing reactive routing schemes, to provide energy efficient and reliable routing of data packets in the complex 3-D sensor networks for multimedia applications. The major attraction of ER3 is its backoff scheme, which occurs in the route discovery phase. In backoff scheme robust pilot paths formed between the source and destination are calculated to enable cooperative forwarding of the data packets. The data packets in ER3 are forwarded greedily to the destination from the source and doesn’t require any prior location information of the nodes. The encompassing simulations suggest that the ER3 outperforms the existing routing protocols on the basis of energy efficiency, low latency and high packet delivery ratio.

     

一种基于Mesh结构Overlay网络的构建算法

Overlay网络是一种构建在IP层网络之上的,由端系统之间的逻辑连接构成的应用层网络。因为Overlay网络易于构建、管理灵活和可扩展性强,在实现Internet上的多种应用中发挥了越来越重要的作用。但是,Overlay网络的连接延时长、抖动大,而且容易形成Overlay网络逻辑连接共享物理链路瓶颈的情况,这样的Overlay网络路由效率低而且鲁棒性差,很难保证诸如流媒体这样的实时应用的Qos要求。文章提出了一种基于Mesh结构的Overlay网络的构建算法。该算法运用了地标聚类和相关路径选择策略,目的是建立一个适应物理拓扑、适用于实时大流量业务的Overlay网络。算法规定当一个节点要加入Overlay网络时,通过测量地标使物理拓扑距离较近的节点相互连接,并且进一步地选择相对独立的多条连接,优化了邻居节点选择、Overlay网络的构建过程。实验结果表明本算法构建的Overlay网络在承载大流量业务时,仍可以保持较大的吞吐量和较好的网络可扩展性。