Ali Mostashari

Measuring the Resilience of the Trans-Oceanic Telecommunication Cable System

Resilience is the ability of the system to both absorb shock as well as to recover rapidly from a disruption so that it can return back to its original service delivery levels or close to it. The trans-oceanic telecommunication fiber-optics cable network that serves as the backbone of the internet is a particularly critical infrastructure system that is vulnerable to both natural and man-made disasters. In this paper, we propose a model to measure the base resiliency of this network, and explore the node to node and the overall resiliency of the network using existing data for demand, capacity and flow information. The submarine cable system is represented by a network model to which hypothetical disruptions can be introduced. The base resiliency of the system can be measured as the ratio of the value delivery of the system after a disruption to the value deliver of the system before a disruption. We further demonstrate how the resiliency of the trans-oceanic telecommunication cable infrastructure is enhanced through vulnerability reduction.

A framework for assessing resiliency of maritime transportation systems

Resiliency can be defined as the ability of the system to bounce back after a shock and return to its normal value delivery levels. In maritime transportation systems (MTS), manmade and natural disruptions reduce the capacity of ports to send and receive goods, which can result in significant negative socio-economic impacts. Implementing resiliency in these systems improves their ability to cope with disruptions hence minimising losses. This paper proposes several schemes that improve resiliency by reducing the systems vulnerability and increasing its adaptive capacity. The impact of the schemes on the systems resiliency metrics are evaluated by applying the methodology of the Networked Infrastructure Resiliency Assessment framework. The framework consists of three stages in which a network model is extracted from the physical network, the resiliency metrics are identified and the system is modelled using network optimisation techniques and a system dynamics model. The disruptions are modelled by reducing the capacity of a port to send and receive goods. Three MTS resiliency metrics are identified, namely tonnage resiliency, time resiliency and cost resiliency. The presented case study assesses resiliency schemes, such as Diversity, Collaboration and Resource Allocation on the three resiliency metrics.

Measuring the resilience of the global internet infrastructure system

Resilience is the ability of the system to both absorb shock as well to recover rapidly from a disruption so that it can return back to its original service delivery levels or close to it. In the aftermath of 9/11 and Hurricane Katrina, there has been an increasing interest in infrastructure resilience. The global submarine fiber optics cable network that serves as the backbone of the internet is a particularly critical infrastructure system that is vulnerable to both natural and man-made disasters. In this paper, we propose a model to measure the base resiliency of this global network, and explore the node to node and global resiliency of the network using existing data demand, capacity and flow information. The base resiliency of the system can be measured as the value delivery of the system after a disruption to the value deliver of the system before a disruption. We further demonstrate how the resiliency of the global internet infrastructure is enhanced through reducing the network vulnerability and increasing its adaptive capacity.

Conceptual Modeling of the Impact of Smart Cities on Household Energy Consumption

Abstract Smart cities provide citizens with information on various urban services and allow them to track the impact of their resource consumption on the overall sustainability of their city. The premise of smart cities is that with improved access to information on resource consumption, residents make better use of those resources, resulting in increased sustainability of the city. This paper explores the influence of the smart city technologies on individuals’ resource consumption behavior, in particular on energy consumption, aiming at achieving environmentally sustainable development. This approach combines systems thinking with existing social science theories, such as cognitive and learning theories, to explore the impact of smart city information on individual decision-making and behavioral change. Using a CLIOS (complex, large-scale, interconnected, open, and sociotechnical) model, a conceptual soft systems model, the paper explores the impact of smart city technologies on behavioral change of households with regards to energy consumption.

A Risk Management-based Decision Analysis Framework for resilience in Maritime Infrastructure and Transportation Systems

This research is an effort to develop a Risk Management-based Decision Analysis (RMDA) Framework based on the common fundamental elements that define the nature of resilience in Maritime Infrastructure and Transportation Systems (MITS). While developing a systematic process for making strategic and investment decisions, RMDA enables the decision-makers to identify, analyze, and prioritize risks involved in MITS operations; to define ways for risk mitigation, plan for contingencies, and devise mechanisms for continuously monitoring and controlling risk factors and threats to the system. Our suggested RMDA framework utilizes a Decision Tree Analysis (DTA) methodology for assessing the cost-effectiveness of the devised strategies.

Measuring systems security

Security metrics have evolved side by side with the advent of security tools and techniques. They have been derived from the techniques rather than specified as system requirements. This paper surveys the evolution and state of the practice of security metrics from both a technical and historical perspective. It describes the evolution of currently popular security metrics, and classifies them to illustrate their utility in systems engineering verification and validation activities. It provides criteria with which to evaluate security metrics based on system purpose and architecture. The criteria are illustrated using a case study of Cloud System security. ©2012 Wiley Periodicals, Inc. Syst Eng 16:

Assessing resilience in a regional road-based transportation network

Resilience deals with the response of the system in the face of shock and its ability to continue to provide the expected service delivery levels. In the transportation infrastructure, system shocks due to man-made and natural causes occur frequently and result in substantial economic losses; it is therefore crucial to enhance the resilience of this infrastructure. Improving the resilience of systems creates a need for developing metrics that measure the current resilience of the system and provides a benchmark for evaluating different strategies for improving resilience. In this paper, we propose a framework for assessing the resilience of a regional road network. The methodology introduced in this paper is the Networked Infrastructure Resilience Assessment (NIRA) framework, which allows decision-makers to assess the resilience of networked infrastructures from a multi-metric perspective. The resilience metrics measure the impact of disruptions on the system performance measures. The three identified metrics for road networks are the travel time resilience, environmental resilience and cost resilience. The resilience values are measured by introducing hypothetical disruptions to a network model of a regional transportation network. The NIRA framework is applied to the transportation corridor between Boston and New York City. We also investigate the impact of disruptions on the travellers mode choice.

Resilience Analysis of Soft Infrastructure Systems

Abstract Infrastructure resilience is often associated with the ability of the hard infrastructure or physical system to cope with severe disruptions; however, the institutions and enterprises that make up the soft infrastructure systems are also prone to crises. Incorporating resilience aids systems to cope with crises and recover from disruptive events, which is not possible without an organizational foundation that is able to cope with and respond to crisis. Additionally, metrics enable stakeholders to assess the effectiveness of resilience strategies and show their added value. This paper outlines a methodology for assessing resilience of soft infrastructure using social network analysis. The methodology is applied to the National Intelligent Transportation System (ITS) where the logical architecture is viewed as a network, and the centrality measures are used to define the systems resilience metrics.

Developing a stakeholder-assisted agile CONOPS development process

Concepts of Operations (CONOPS) are documents describing the characteristics and intended usage of proposed and existing systems. They provide information about the requirements and future desired states the project aims to achieve. We reviewed 22 recent CONOPS from government and private sector institutions to ascertain the current approach to CONOPS development. Based on the CONOPS review and research literature, we highlight three key areas, stakeholder involvement, shared mental models, and visualization, through which the development process may be improved. Moreover, we suggest that the development process itself may be transformed into an agile process that addresses current shortcomings in the key areas. To do so, we propose an agile CONOPS development process conducted through three iteration-driven phases and present corresponding research and commercial tools that may be leveraged at each phase. As such, putting this agile process into effect may reduce development time, improve effectiveness, and change the perception of the CONOPS from a burdensome documentation procedure to an invaluable resource throughout the system lifecycle.

Influence of component uncertainty on reliability assessment of systems with continuous states

Existing reliability evaluation methods are based on the availability of knowledge about component states. However, component states are often uncertain or unknown, especially during the early stages of the development of new systems. In such cases it is important to understand how uncertainties will affect system reliability assessment. Another shortcoming of existing methods is that they only consider systems whose components have discrete states. For those whose components have continuous states, these methods may not be applicable. Using Monte-Carlo simulation, this paper proposed a method to assess the reliability of systems with continuous distribution of component states. This method will also be useful when we do not have enough knowledge on component states and related probabilities. Comparison of two examples proves that component uncertainty has significant influence on the assessment of system reliability.