Regulating Highly Automated Robot Ecologies: Insights from Three User Studies

Highly automated robot ecologies (HARE), or societies of independent autonomous robots or agents, are rapidly becoming an important part of much of the world's critical infrastructure. As with human societies, regulation, wherein a governing body designs rules and processes for the society, plays an important role in ensuring that HARE meet societal objectives. However, to date, a careful study of interactions between a regulator and HARE is lacking. In this paper, we report on three user studies which give insights into how to design systems that allow people, acting as the regulatory authority, to effectively interact with HARE. As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy. Our results show that regulator power, decision support, and adaptive autonomy can each diminish the social welfare of HARE, and hint at how these seemingly desirable mechanisms can be designed so that they become part of successful HARE.Comment: 10 pages, 7 figures, to appear in the 5th International Conference on Human Agent Interaction (HAI-2017), Bielefeld, German

Estimating the Propagation of Interdependent Cascading Outages with Multi-Type Branching Processes

In this paper, the multi-type branching process is applied to describe the statistics and interdependencies of line outages, the load shed, and isolated buses. The offspring mean matrix of the multi-type branching process is estimated by the Expectation Maximization (EM) algorithm and can quantify the extent of outage propagation. The joint distribution of two types of outages is estimated by the multi-type branching process via the Lagrange-Good inversion. The proposed model is tested with data generated by the AC OPA cascading simulations on the IEEE 118-bus system. The largest eigenvalues of the offspring mean matrix indicate that the system is closer to criticality when considering the interdependence of different types of outages. Compared with empirically estimating the joint distribution of the total outages, good estimate is obtained by using the multitype branching process with a much smaller number of cascades, thus greatly improving the efficiency. It is shown that the multitype branching process can effectively predict the distribution of the load shed and isolated buses and their conditional largest possible total outages even when there are no data of them.Comment: Accepted by IEEE Transactions on Power System

Computer Immunodeficiency: Analogy between Computer Security and HIV

Current security systems are designed to prevent foreseeable attacks. Those security systems do not prevent effectively the more emergent types of attacks, like a botnet, whose presence and behavior is difficult to predict. In order to predominate those types of attacks, we advocate an adaptive security approach based on the animal immune system. But since those sophisticated attacks can also be directed at the security systems themselves, leading to computer immunodeficiency, like HIV, in this paper we propose a protocol that protects the immune system itself. This approach discriminates between attacks on the security systems, which are part of the computer immune system, and attacks on other vital computer systems in an information infrastructure

Socially-integrated resilience in building-level water networks using smart microgrid+net

Environmental change and natural events can impact on multiple dimensions of human life; economic, social, political, physical (built) and natural (ecosystems) environments. Water distribution networks cover both the built and natural realms and are as such inherently vulnerable to accidental or deliberate physical, natural, chemical, or biological threats. An example of such threats include flooding. The damage to water networks from flooding at the building level can include disrupted supply, pipe damage, sink and sewer overflows, fittings and appliance malfunctions etc. as well as the consequential socio-economic loss and distress. It has also been highlighted that the cost of damage caused by disasters including flooding can be correlated to the warning-time given before it occurs. Therefore, contiguous and continuous preparedness is essential to sustain disaster resilience. This paper presents an early stage review to: 1. Understand the challenges and opportunities posed by disaster risks to critical infrastructure at the building level. 2. Examine the role and importance of early warnings within the smart systems context to promote anticipatory preparedness and reduce physical, economic, environmental and social vulnerability 3. Review the opportunities provided by smart water microgrid/net to deliver such an early warning system and 4. Define the basis for a socially-integrated framework for resilience in building water networks based on smart water micro grids and micronets. The objective is to establish the theoretical approach for smart system integration for risk mitigation in water networks at the building level. Also, to explore the importance and scope integration of other social-political dimensions within such framework and associated solutions. The findings will inform further studies to address the gaps in understanding the disaster risks in micro water infrastructure e.g. flooding, and; to develop strategies and systems to strengthen disaster preparedness for effective response and anticipatory action for such risks

Quantitative modeling of reliability and survivability for cyber-physical power systems

Critical infrastructure systems are increasingly reliant on cyber infrastructure that enables intelligent real-time control of physical components. This cyber infrastructure utilizes environmental and operational data to provide decision support intended to increase the efficacy and reliability of the system and facilitate mitigation of failure. Realistic imperfections, such as corrupt sensor data, software errors, or failed communication links can cause failure in a functional physical infrastructure, defying the purpose of intelligent control. As such, justifiable reliance on cyber-physical critical infrastructure is contingent on rigorous investigation of the effect of intelligent control, including modeling and simulation of failure propagation within the cyber-physical infrastructure. To this end, this thesis investigates the reliability and survivability of a cyber-physical power grid based on the IEEE 9-bus test system. The research contributions include quantitative modeling of both non-functional attributes, based on data from N-1 contingency analysis that considers failures in physical and cyber components of the system. The resulting survivability model is utilized in determining the importance of each transmission line. The final research contribution is identification of optimal recovery strategies for the system, where the objective is to maintain the highest possible survivability in the course of recovery. --Abstract, page iii

Network Interdependency Modeling for Risk Assessment on Built Infrastructure Systems

As modern infrastructures become more interconnected, the decision-making process becomes more difficult because of the increased complexity resulting from infrastructure interdependencies. Simulation and network modeling provide a way to understand system behavior as a result of interdependencies. One area within the asset management literature that is not well covered is infrastructure system decay and risks associated with that decay. This research presents an enhanced version of Haimes\u27 input-output inoperability model (IIM) in the analysis of built infrastructure systems. Previous applications of the IIM characterized infrastructure at the national level utilizing large economic databases. This study develops a three-phased approach that takes component level data stored within geographic information systems (GIS) to provide a metric for network interdependency across a municipal level infrastructure. A multi-layered approach is proposed which leverages the layered data structure of GIS. Furthermore, Monte Carlo simulation using stochastic decay estimates shows how infrastructure risk as a result of interdependency effects changes over time. Such an analysis provides insight to infrastructure asset managers on the impact of policy and strategy decision-making regarding the maintenance and management of their infrastructure systems

A Balance between Ideals and Reality — Establishing and Evaluating a Resilient City Indicator System for Central Chinese Cities

Recent years have seen a gradual shift in focus of international policies from a national and regional perspective to that of cities, a shift which is closely related to the rapid urbanization of developing countries. As revealed in the 2011 Revision of the World Urbanization Prospects published by the United Nations, 51% of the global population (approximately 3.6 billion people) lives in cities. The report predicts that by 2050, the world’s urban population will increase by 2.3 billion, making up 68% of the population. The growth of urbanization in the next few decades is expected to primarily come from developing countries, one third of which will be in China and India. With rapid urbanization and the ongoing growth of mega cities, cities must become increasingly resilient and intelligent to cope with numerous challenges and crises like droughts and floods arising from extreme climate, destruction brought by severe natural disasters, and aggregated social contradictions resulting from economic crises. All cities face the urban development dynamics and uncertainties arising from these problems. Under such circumstances, cities are considered the critical path from crisis to prosperity, so scholars and organizations have proposed the construction of “resilient cities.” On the one hand, this theory emphasizes cities’ defenses and buffering capacity against disasters, crises and uncertainties, as well as recovery after destruction; on the other hand, it highlights the learning capacity of urban systems, identification of opportunities amid challenges, and maintenance of development vitality. Some scholars even believe that urban resilience is a powerful supplement to sustainable development. Hence, resilience assessment has become the latest and most important perspective for evaluating the development and crisis defense capacity of cities. Rather than a general abstract concept, urban resilience is a comprehensive measurement of a city’s level of development. The dynamic development of problems is reflected through quantitative indicators and appraisal systems not only from the perspective of academic research, but also governmental policy, so as to scientifically guide development, and measure and compare cities’ development levels. Although international scholars have proposed quantitative methods for urban resilience assessment, they are however insufficiently systematic and regionally adaptive for China’s current urban development needs. On the basis of comparative study on European and North American resilient city theories, therefore, this paper puts forwards a theoretical framework for resilient city systems consistent with China’s national conditions in light of economic development pressure, natural resource depletion, pollution, and other salient development crises in China. The key factors influencing urban resilience are taken into full consideration; expert appraisal is conducted based on the Delphi Method and the analytic hierarchy process (AHP) to design an extensible and updatable resilient city evaluation system which is sufficiently systematic, geographically adaptable, and sustainable for China’s current urban development needs. Finally, Changsha is taken as the main case for empirical study on comprehensive evaluation of similar cities in Central China to improve the indicator system