Formal analyses of incentives for compliance with network protocols often appeal to game-theoretic models and concepts. Applications of game-theoretic analysis to network security have generally been limited to highly stylized models, where simplified environments enable tractable study of key strategic variables. We propose a simulation-based approach to game-theoretic analysis of protocol compliance, for scenarios with large populations of agents and large policy spaces. We define a general procedure for systematically exploring a structured policy space, directed expressly to resolve the qualitative classification of equilibrium behavior as compliant or non-compliant. The techniques are illustrated and exercised through an extensive case study analyzing compliance incentives for introduction-based routing. We find that the benefits of complying with the protocol are particularly strong for nodes subject to attack, and the overall compliance level achieved in equilibrium, while not universal, is sufficient to support the desired security goals of the protocol.
Routing strategies under the aegis of dynamic traffic assignment have been proposed in the literature to optimize system performance. However, challenges have persisted in their deployment ability and effectiveness due to inherent strong assumptions on traveler behavior and availability of network-level real-time traffic information, and the high computational burden associated with computing network-wide flows in real-time. This study proposes an incentive-based decentralized routing strategy to nudge the network performance closer to the system optimum for the context where all vehicles are …
We consider a two-road dynamic routing game where the state of one of the roads (the "risky road") is stochastic and may change over time. This generates room for experimentation. A central planner may wish to induce some of the (finite number of atomic) agents to use the risky road even when the expected cost of travel there is high in order to obtain accurate information about the state of the road. Since agents are strategic, we show that in order to generate incentives for experimentation the central planner however needs to limit the number of agents using the risky road when the expected…
We present an incentive model for route distribution in the context of path vector routing protocols and we focus on the Border Gateway Protocol (BGP). BGP is the de-facto protocol for interdomain routing on the Internet. We model BGP route distribution and computation using a game in which a BGP speaker advertises its prefix to its direct neighbors promising them a reward for further distributing the route deeper into the network, the neighbors do the same thing with their neighbors, and so on. The result of this cascaded route distribution is an advertised prefix and hence reachability of th…
Off-chain protocols constitute one of the most promising approaches to solve the inherent scalability issue of blockchain technologies. The core idea is to let parties transact on-chain only once to establish a channel between them, leveraging later on the resulting channel paths to perform arbitrarily many peer-to-peer transactions off-chain. While significant progress has been made in terms of proof techniques for off-chain protocols, existing approaches do not capture the game-theoretic incentives at the core of their design, which led to overlooking significant attack vectors like the Worm…
School of Mathematics and Statistics, Northwestern Polytechnical University（西北工业大学数学与统计学院）；Department of Applied Mathematics, University of Twente（特温特大学应用数学系）
How can a system designer exploit system-level knowledge to derive incentives to optimally influence social behavior? The literature on network routing contains many results studying the application of monetary tolls to influence behavior and improve the efficiency of self-interested network traffic routing. These results typically fall into two categories: (1) optimal tolls which incentivize socially-optimal behavior for a known realization of the network and population, or (2) robust tolls which provably reduce congestion given uncertainty regarding networks and user types, but may fail to o…
How can a social planner adaptively incentivize selfish agents who are learning in a strategic environment to induce a socially optimal outcome in the long run? We propose a two-timescale learning dynamics to answer this question in both atomic and non-atomic games. In our learning dynamics, players adopt a class of learning rules to update their strategies at a faster timescale, while a social planner updates the incentive mechanism at a slower timescale. In particular, the update of the incentive mechanism is based on each player's externality, which is evaluated as the difference between th…
We study a routing game in an environment with multiple heterogeneous information systems and an uncertain state that affects edge costs of a congested network. Each information system sends a noisy signal about the state to its subscribed traveler population. Travelers make route choices based on their private beliefs about the state and other populations' signals. The question then arises, "How does the presence of asymmetric and incomplete information affect the travelers' equilibrium route choices and costs?'' We develop a systematic approach to characterize the equilibrium structure, and …
Selfish behaviors are common in self-organized Mobile Ad hoc Networks (MANETs) where nodes belong to different authorities. Since cooperation of nodes is essential for routing protocols, various methods have been proposed to stimulate cooperation among selfish nodes. In order to provide sufficient incentives, most of these methods pay nodes a premium over their actual costs of participation. However, they lead to considerably large overpayments. Moreover, existing methods ignore mobility of nodes, for simplicity. However, owing to the mobile nature of MANETs, this assumption seems unrealistic.…
We study learning dynamics induced by myopic travelers who repeatedly play a routing game on a transportation network with an unknown state. The state impacts cost functions of one or more edges of the network. In each stage, travelers choose their routes according to Wardrop equilibrium based on public belief of the state. This belief is broadcast by an information system that observes the edge loads and realized costs on the used edges, and performs a Bayesian update to the prior stage's belief. We show that the sequence of public beliefs and edge load vectors generated by the repeated play …
In the current intensively changing technological environment, wireless network operators try to manage the increase of global traffic, optimizing the use of the available resources. This involves associating each user to one of its reachable wireless networks; a decision that can be made on the user side, in which case inefficiencies stem from user selfishness. This paper aims at correcting that efficiency loss through the use of a one-dimensional incentive signal, interpreted as a price. While the so-called Pigovian taxes allow to deal with homogeneous users, we consider here two classes wit…
Today mobile users are intensively interconnected thanks to the emerging mobile social networks, where they share location-based information with each other when traveling on different routes and visit different areas of the city. In our model the information collected is aggregated over all users' trips and made publicly available as a public good. Due to information overlap, the total useful content amount increases with the diversity in path choices made by the users, and it is crucial to motivate selfish users to choose different paths despite the potentially higher costs associated with t…
Delay Tolerant Networks (DTNs) rely on the cooperation of nodes in a network to forward a message from its source to its destination. Most of previous studies on DTNs have focused on the design of routing schemes under the hypothesis that each relay node is willing to participate in the forwarding process. However, the delivery of a message incurs energy and memory costs. In this paper we handle the problem of how to incentivize mobile nodes to participate in relaying messages using a reward mechanism. We consider heterogeneous relay nodes where the cost for taking part in the forwarding proce…
In congestion games, users make myopic routing decisions to jam each other, and the social planner with the full information designs mechanisms on information or payment side to regulate. However, it is difficult to obtain time-varying traffic conditions, and emerging crowdsourcing platforms (e.g., Waze and Google Maps) provide a convenient way for mobile users travelling on the paths to learn and share the traffic conditions over time. When congestion games meet mobile crowdsourcing, it is critical to incentive selfish users to change their myopic routing policy and reach the best exploitatio…
The Internet is a loose amalgamation of independent service providers acting in their own self-interest. We examine the implications of this economic reality on peering relationships. Specifically, we consider how the incentives of the providers might determine where they choose to interconnect with each other. We consider a game where two selfish network providers must establish peering points between their respective network graphs, given knowledge of traffic conditions and a nearest-exit routing policy for out-going traffic, as well as costs based on congestion and peering connectivity. We …
A Necessary and Sufficient Condition for the Existence of Potential Functions for Heterogeneous Routing Games
ACCESS Linnaeus Center, School of Electrical Engineering, KTH Royal Institute of Technology（KTH皇家理工学院电气工程学院）；department of Electrical Engineering and Computer Sciences, University of California at Berkeley（加州大学伯克利分校电气工程与计算机科学系）；department of Civil and Environmental Engineering, University of California at Berkeley（加州大学伯克利分校土木与环境工程系）
We ask if it is possible to positively influence social behavior with no risk of unintentionally incentivizing pathological behavior. In network routing problems, if network traffic is composed of many individual agents, it is known that self-interested behavior among the agents can lead to suboptimal network congestion. We study situations in which a system planner charges monetary tolls for the use of network links in an effort to incentivize efficient routing choices by the users, but in which the users' sensitivity to tolls is heterogeneous and unknown. We seek locally-computed tolls that …
