Bottleneck Routing Games with Low Price of Anarchy

We study {\em bottleneck routing games} where the social cost is determined by the worst congestion on any edge in the network. In the literature, bottleneck games assume player utility costs determined by the worst congested edge in their paths. However, the Nash equilibria of such games are inefficient since the price of anarchy can be very high and proportional to the size of the network. In order to obtain smaller price of anarchy we introduce {\em exponential bottleneck games} where the utility costs of the players are exponential functions of their congestions. We find that exponential bottleneck games are very efficient and give a poly-log bound on the price of anarchy: $O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the players' strategy sets and $E$ is the set of edges in the graph. By adjusting the exponential utility costs with a logarithm we obtain games whose player costs are almost identical to those in regular bottleneck games, and at the same time have the good price of anarchy of exponential games.Comment: 12 page

Congestion Games with Complementarities

We study a model of selfish resource allocation that seeks to incorporate dependencies among resources as they exist in modern networked environments. Our model is inspired by utility functions with constant elasticity of substitution (CES) which is a well-studied model in economics. We consider congestion games with different aggregation functions. In particular, we study $L_p$ norms and analyze the existence and complexity of (approximate) pure Nash equilibria. Additionally, we give an almost tight characterization based on monotonicity properties to describe the set of aggregation functions that guarantee the existence of pure Nash equilibria.Comment: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-57586-5_1

Provider and peer selection in the evolving internet ecosystem

The Internet consists of thousands of autonomous networks connected together to provide end-to-end reachability. Networks of different sizes, and with different functions and business objectives, interact and co-exist in the evolving "Internet Ecosystem". The Internet ecosystem is highly dynamic, experiencing growth (birth of new networks), rewiring (changes in the connectivity of existing networks), as well as deaths (of existing networks). The dynamics of the Internet ecosystem are determined both by external "environmental" factors (such as the state of the global economy or the popularity of new Internet applications) and the complex incentives and objectives of each network. These dynamics have major implications on how the future Internet will look like. How does the Internet evolve? What is the Internet heading towards, in terms of topological, performance, and economic organization? How do given optimization strategies affect the profitability of different networks? How do these strategies affect the Internet in terms of topology, economics, and performance? In this thesis, we take some steps towards answering the above questions using a combination of measurement and modeling approaches. We first study the evolution of the Autonomous System (AS) topology over the last decade. In particular, we classify ASes and inter-AS links according to their business function, and study separately their evolution over the last 10 years. Next, we focus on enterprise customers and content providers at the edge of the Internet, and propose algorithms for a stub network to choose its upstream providers to maximize its utility (either monetary cost, reliability or performance). Third, we develop a model for interdomain network formation, incorporating the effects of economics, geography, and the provider/peer selections strategies of different types of networks. We use this model to examine the "outcome" of these strategies, in terms of the topology, economics and performance of the resulting internetwork. We also investigate the effect of external factors, such as the nature of the interdomain traffic matrix, customer preferences in provider selection, and pricing/cost structures. Finally, we focus on a recent trend due to the increasing amount of traffic flowing from content providers (who generate content), to access providers (who serve end users). This has led to a tussle between content providers and access providers, who have threatened to prioritize certain types of traffic, or charge content providers directly -- strategies that are viewed as violations of "network neutrality". In our work, we evaluate various pricing and connection strategies that access providers can use to remain profitable without violating network neutrality.Ph.D.Committee Chair: Dovrolis, Constantine; Committee Member: Ammar, Mostafa; Committee Member: Feamster, Nick; Committee Member: Willinger, Walter; Committee Member: Zegura, Elle

Techniques d'ingénierie de trafic dynamique pour l'internet

Network convergence and new applications running on end-hosts result in increasingly variable and unpredictable traffic patterns. By providing origin-destination pairs with several possible paths, Dynamic Load-Balancing (DLB) has proved itself an excellent tool to face this uncertainty. The objective in DLB is to distribute traffic among these paths in real-time so that a certain objective function is optimized. In these dynamic schemes, paths are established a priori and the amount of traffic sent through each of them depends on the current traffic demand and network condition. In this thesis we study and propose various DLB mechanisms, differing in two important aspects. The first difference resides in the assumption, or not, that resources are reserved for each path. The second lies on the objective function, which clearly dictates the performance obtained from the network. However, a performance benchmarking of the possible choices has not been carried out so far. In this sense, for the case in which no reservations are performed, we study and compare several objective functions, including a proposal of ours. We will also propose and study a new distributed algorithm to attain the optimum of these objective functions. Its advantage with respect to previous proposals is its complete self-configuration (i. E. Convergence is guaranteed without any parametrization). Finally, we present the first complete comparative study between DLB and Robust Routing (a fixed routing configuration for all possible traffic demands). In particular, we analyze which scheme is more convenient in each given situation, and highlight some of their respective shortcomings and virtues.Avec la multiplication des services dans un même réseau et les diversités des applications utilisées par les usagers finaux, le trafic transporté est devenu très complexe et dynamique. Le Partage de la Charge Dynamique (PCD) constitue une alternative intéressante pour résoudre cette problématique. Si une paire Source-Destination est connectée par plusieurs chemins, le problème est le suivant : comment distribuer le trafic parmi ces chemins de telle façon qu’une fonction objective soit optimisé. Dans ce cas les chemins sont fixés a priori et la quantité de trafic acheminée sur chaque route est déterminée dynamiquement en fonction de la demande de trafic et de la situation actuelle du réseau. Dans cette thèse nous étudions puis nous proposons plusieurs mécanismes de PCD. Tout d'abord, nous distinguons deux types d’architecture : celles dans lesquelles les ressources sont réservées pour chaque chemin, et celles pour lesquelles aucune réservation n'est effectuée. La simplification faite dans le premier type d’architecture nous permet de proposer l'utilisation d'un nouveau mécanisme pour gérer les chemins. Partant de ce mécanisme, nous définissons un nouvel algorithme de PCD. Concernant la deuxième architecture, nous étudions et comparons plusieurs fonctions objectives. À partir de notre étude, nous proposons un nouvel algorithme distribué permettant d’atteindre l'optimum de ces fonctions objectives. La principale caractéristique de notre algorithme, et son avantage par rapport aux propositions antérieures, est sa capacité d'auto-configuration, dans la mesure où la convergence de l'algorithme est garantie sans aucun besoin de réglage préalable de ses paramètres

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Service-Driven Networking

This thesis presents our research on service-driven networking, which is a general design framework for service quality assurance and integrated network and service management in large scale multi-domain networks. The philosophy is to facilitate bi-party open participation among the users and the providers of network services in order to bring about better service customization and quality assurance, without sacrificing the autonomy and objectives of the individual entities. Three primary research topics are documented: service composition and adaptation, self-stabilization in uncoordinated environment, and service quality modeling. The work involves theoretical analysis, algorithm design, and simulations as evaluation methodology

Day-to-day Traffic Dynamics with Strategic Commuters

In the era of connected and automated mobility, commuters (connected drivers or automated vehicles) will possess strong computation capability and their travel decisions can be algorithmic and strategic. This paper investigates the day-to-day travel choice evolution of such strategic commuters who are capable of long-term planning and computation. We model the commute problem as a mean field game and examine the mean field equilibrium to derive the evolution of the network traffic flow pattern. The proposed model is general and can be tailored to various travel choices such as route or departure time. Under various conditions, we prove the existence and uniqueness of the day-to-day equilibrium traffic evolution pattern as well as its convergence to stationarity. Connection with traditional Wardropian equilibrium is established by examining the physical interpretation of the stationary solution