Local majorities, coalitions and monopolies in graphs: a review

AbstractThis paper provides an overview of recent developments concerning the process of local majority voting in graphs, and its basic properties, from graph theoretic and algorithmic standpoints

Mixed-integer Programming Methods for Modeling and Optimization of Cascading Processes in Complex Networked Systems

Dynamics and growth of many natural and man-made systems can be represented by large-scale complex networks. Entity interactions and community interconnections within complex networks increase the level of difficulty for the investigation on structural network properties such as robustness, vulnerability and resilience. In this dissertation, we develop methodologies based on mixed-integer programming techniques to solve challenging optimization problems that model cascading processes in complex networked systems. In particular, we seek to provide decision making recommendations for problems related to different types of cascading processes in networks commonly considered in a variety of applications: interdependent infrastructure networks and social networks. In the first part, we propose a novel optimization model to enhance the resilience against cascading failure by mitigation and restoration in interdependent networks. We derive a polynomial class of valid inequalities from the cascading constraints and reformulate the substructure that describes capacity restriction to guarantee integral solutions. The computational experiments illustrate that our strengthened formulation outperforms the default setting of a commercial solver on all tested instances. Next, we study the least cost influence maximization problem that arises in social network analytics. We investigate the polyhedral properties of a substructure that is a relaxation of the mixed 0-1 knapsack polyhedron. We give three exponential class of facet-defining inequalities from this substructure and an exact polynomial time separation algorithm for the inequalities. In addition, we propose another new class of strong valid inequalities that dominates the cycle elimination constraints. Through the computational experiments, we demonstrate that a delayed cut generation algorithm that exploits these inequalities is very effective to solve the problem under different settings of network size, density and connectivity

The Economics of Wholesale Electricity Markets

This dissertation is based on four articles. Chapter 2 is based on Growitsch and Müsgens (2005). In this chapter, we analyze the development of household electricity prices since the liberalization of the market in 1998. The chapter covers all components of the price, the wholesale component, and the transportation and distribution networks. We also discuss the developments of taxes and subsidies in the electricity market. The main result is that the liberalization appears to have had no significant impact on total consumer prices, as prices in 2004 are nearly the same as in 1998. However, a deeper analysis reveals significant differences between the price components: wholesale prices, which are at the focus of the other chapters in this dissertation, decreased significantly directly after the liberalization took place, but increased from 2001 to 2004. The latter effect is discussed in chapter 3. Despite this increase, wholesale prices are still lower in 2004 than they were in 1998. The costs for transportation and distribution networks decreased slightly but steadily over time. The prices of other cost components (Renewable energy act, CHP subsidies, taxes ), however, rose sharply after the liberalization. This result has serious implications, as it means that insubstantial reductions in household prices do not reveal much about the success of liberalization or the behavior of the electricity supply industry. Chapter 3 is based on Müsgens (2007). The chapter presents a model to calculate system marginal costs in electricity markets. The model is a dynamic linear optimization model including start-up costs, hydro storage and pump storage dispatch, and international power exchange in the equations. We apply this model to the German power exchange for the period from June 2000 to June 2003 and perform a competitive benchmarking study. We find that prices are very close to our model-derived competitive benchmark in a first period until August 2001: the difference between prices and benchmark is only 2% in this period. In the following period, observed market prices rise significantly; this rise is not reflected in the competitive benchmark: prices are nearly 50% above the competitive benchmark in this second period. We also show that this deviation mainly comes from the high demand periods in which capacity is scarce. This is in accordance with the theories of market power. Furthermore, the chapter contains several scenarios quantifying the price effects of non-convexities and other dynamic elements. Chapter 4 is based on Müsgens and Neuhoff (2005). As in chapter 3, we present a linear optimization model to determine the optimal dispatch. The model is extended to allow the analysis of the uncertainty brought into the market by wind power generation. We represent uncertainty by applying stochastic programming with recourse. We parameterize the model with historical data from the German power market and find that the short term costs for the integration of wind power are low, as there is sufficient capacity during most periods to provide balancing services. Chapter 5 is based on Kuntz and Müsgens (2005). The chapter presents a formal in-depth analysis of the effects of start-up costs on electricity markets. The chapter starts from a simplified version of the optimization problem in chapter 4. Using appropriate transformations (dualization of the original problem, rephrasing the dual and reconverting it into a modified primal problem), we can prove that the impact of start-up costs on the average price is very small, which was already suggested by the empirical analyses in chapters 3 and 4. Chapter 6 concludes the dissertation

Conclave: secure multi-party computation on big data (extended TR)

Secure Multi-Party Computation (MPC) allows mutually distrusting parties to run joint computations without revealing private data. Current MPC algorithms scale poorly with data size, which makes MPC on "big data" prohibitively slow and inhibits its practical use. Many relational analytics queries can maintain MPC's end-to-end security guarantee without using cryptographic MPC techniques for all operations. Conclave is a query compiler that accelerates such queries by transforming them into a combination of data-parallel, local cleartext processing and small MPC steps. When parties trust others with specific subsets of the data, Conclave applies new hybrid MPC-cleartext protocols to run additional steps outside of MPC and improve scalability further. Our Conclave prototype generates code for cleartext processing in Python and Spark, and for secure MPC using the Sharemind and Obliv-C frameworks. Conclave scales to data sets between three and six orders of magnitude larger than state-of-the-art MPC frameworks support on their own. Thanks to its hybrid protocols, Conclave also substantially outperforms SMCQL, the most similar existing system.Comment: Extended technical report for EuroSys 2019 pape

A complex systems perspective on innovation, investment and regulation of evolving telecommunications networks

This thesis is a Doctoral Thesis of the International Executive Doctorate Programme (DBA) at the School of Management, Cranfield University, UK. The purpose of the study is to present the results of the research dedicated to the topic of Infrastructure Sharing, a common method to make use of the limited infrastructure resources of many stakeholders. The research aims to develop a decision support tool for a National Regulating Authority (NRA) on the basis of a software simulation representing infrastructure in use as complex systems consisting of agent and infrastructure networks. By applying a computational Agent-Based Modelling (ABM) approach to policy decisions, i.e. influence of Duct and Pole Access (DPA) to incumbent telecommunication infrastructures, the research investigates regulatory considerations that stimulate the development of alternative networks. The final deliverable of the research is a simulation tool that provides a solid foundation for simulating experiments, which allows analysis of demand for broadband services by different subgroups of users. The results of the study are of value for regulators, practitioners, representatives of telecommunication and other network industries, and scholars who deal with the topic of sustainable infrastructure development and recognise the value of a complex system perspective