A Study of Truck Platooning Incentives Using a Congestion Game

We introduce an atomic congestion game with two types of agents, cars and trucks, to model the traffic flow on a road over various time intervals of the day. Cars maximize their utility by finding a trade-off between the time they choose to use the road, the average velocity of the flow at that time, and the dynamic congestion tax that they pay for using the road. In addition to these terms, the trucks have an incentive for using the road at the same time as their peers because they have platooning capabilities, which allow them to save fuel. The dynamics and equilibria of this game-theoretic model for the interaction between car traffic and truck platooning incentives are investigated. We use traffic data from Stockholm to validate parts of the modeling assumptions and extract reasonable parameters for the simulations. We use joint strategy fictitious play and average strategy fictitious play to learn a pure strategy Nash equilibrium of this game. We perform a comprehensive simulation study to understand the influence of various factors, such as the drivers' value of time and the percentage of the trucks that are equipped with platooning devices, on the properties of the Nash equilibrium.Comment: Updated Introduction; Improved Literature Revie

On the characterization and computation of Nash equilibria on parallel networks with horizontal queues

Abstract-We study inefficiencies in parallel networks with horizontal queues due to the selfish behavior of players, by comparing social optima to Nash equilibria. The article expands studies on routing games which traditionally model congestion with latency functions that increase with the flow on a particular link. This type of latency function cannot capture congestion effects on horizontal queues. Latencies on horizontal queues increase as a function of density, and flow can decrease with increasing latencies. This class of latency functions arises in transportation networks. For static analysis of horizontal queues on parallel-link networks, we show that there may exist multiple Nash equilibria with different total costs, which contrasts with results for increasing latency functions. We present a novel algorithm, quadratic in the number of links, for computing the Nash equilibrium that minimizes total cost (best Nash equilibrium). The relative inefficiencies of best Nash equilibria are evaluated through analysis of the price of stability, and analytical results are presented for two-link networks. Price of stability is shown to be sensitive to changes in demand when links are near capacity, and congestion mitigation strategies are discussed, motivated by our results

Enable Reliable and Secure Data Transmission in Resource-Constrained Emerging Networks

The increasing deployment of wireless devices has connected humans and objects all around the world, benefiting our daily life and the entire society in many aspects. Achieving those connectivity motivates the emergence of different types of paradigms, such as cellular networks, large-scale Internet of Things (IoT), cognitive networks, etc. Among these networks, enabling reliable and secure data transmission requires various resources including spectrum, energy, and computational capability. However, these resources are usually limited in many scenarios, especially when the number of devices is considerably large, bringing catastrophic consequences to data transmission. For example, given the fact that most of IoT devices have limited computational abilities and inadequate security protocols, data transmission is vulnerable to various attacks such as eavesdropping and replay attacks, for which traditional security approaches are unable to address. On the other hand, in the cellular network, the ever-increasing data traffic has exacerbated the depletion of spectrum along with the energy consumption. As a result, mobile users experience significant congestion and delays when they request data from the cellular service provider, especially in many crowded areas. In this dissertation, we target on reliable and secure data transmission in resource-constrained emerging networks. The first two works investigate new security challenges in the current heterogeneous IoT environment, and then provide certain countermeasures for reliable data communication. To be specific, we identify a new physical-layer attack, the signal emulation attack, in the heterogeneous environment, such as smart home IoT. To defend against the attack, we propose two defense strategies with the help of a commonly found wireless device. In addition, to enable secure data transmission in large-scale IoT network, e.g., the industrial IoT, we apply the amply-and-forward cooperative communication to increase the secrecy capacity by incentivizing relay IoT devices. Besides security concerns in IoT network, we seek data traffic alleviation approaches to achieve reliable and energy-efficient data transmission for a group of users in the cellular network. The concept of mobile participation is introduced to assist data offloading from the base station to users in the group by leveraging the mobility of users and the social features among a group of users. Following with that, we deploy device-to-device data offloading within the group to achieve the energy efficiency at the user side while adapting to their increasing traffic demands. In the end, we consider a perpendicular topic - dynamic spectrum access (DSA) - to alleviate the spectrum scarcity issue in cognitive radio network, where the spectrum resource is limited to users. Specifically, we focus on the security concerns and further propose two physical-layer schemes to prevent spectrum misuse in DSA in both additive white Gaussian noise and fading environments

Uncertainty in Multi-Commodity Routing Networks: When does it help?

We study the equilibrium behavior in a multi-commodity selfish routing game with many types of uncertain users where each user over- or under-estimates their congestion costs by a multiplicative factor. Surprisingly, we find that uncertainties in different directions have qualitatively distinct impacts on equilibria. Namely, contrary to the usual notion that uncertainty increases inefficiencies, network congestion actually decreases when users over-estimate their costs. On the other hand, under-estimation of costs leads to increased congestion. We apply these results to urban transportation networks, where drivers have different estimates about the cost of congestion. In light of the dynamic pricing policies aimed at tackling congestion, our results indicate that users' perception of these prices can significantly impact the policy's efficacy, and "caution in the face of uncertainty" leads to favorable network conditions.Comment: Currently under revie

Design, analysis and optimization of visible light communications based indoor access systems for mobile and internet of things applications

Demands for indoor broadband wireless access services are expected to outstrip the spectrum capacity in the near-term spectrum crunch . Deploying additional femtocells to address spectrum crunch is cost-inefficient due to the backhaul challenge and the exorbitant system maintenance. According to an Alcatel-Lucent report, most mobile Internet access traffic happens indoors. To alleviate the spectrum crunch and the backhaul challenge problems, visible light communication (VLC) emerges as an attractive candidate for indoor wireless access in the 5G architecture. In particular, VLC utilizes LED or fluorescent lamps to send out imperceptible flickering light that can be captured by a smart phone camera or photodetector. Leveraging power line communication and the available indoor infrastructure, VLC can be utilized with a small one-time cost. VLC also facilitates the great advantage of being able to jointly perform illumination and communications. Integration of VLC into the existing indoor wireless access networks embraces many challenges, such as lack of uplink infrastructure, excessive delay caused by blockage in heterogeneous networks, and overhead of power consumption. In addition, applying VLC to Internet-of-Things (IoT) applications, such as communication and localization, faces the challenges including ultra-low power requirement, limited modulation bandwidth, and heavy computation and sensing at the device end. In this dissertation, to overcome the challenges of VLC, a VLC enhanced WiFi system is designed by incorporating VLC downlink and WiFi uplink to connect mobile devices to the Internet. To further enhance robustness and throughput, WiFi and VLC are aggregated in parallel by leveraging the bonding technique in Linux operating system. Based on dynamic resource allocation, the delay performance of heterogeneous RF-VLC network is analyzed and evaluated for two different configurations - aggregation and non-aggregation. To mitigate the power consumption overhead of VLC, a problem of minimizing the total power consumption of a general multi-user VLC indoor network while satisfying users traffic demands and maintaining an acceptable level of illumination is formulated. The optimization problem is solved by the efficient column generation algorithm. With ultra-low power consumption, VLC backscatter harvests energy from indoor light sources and transmits optical signals by modulating the reflected light from a reflector. A novel pixelated VLC backscatter is proposed and prototyped to address the limited modulation bandwidth by enabling more advanced modulation scheme than the state-of-the-art on-off keying (OOK) scheme and allowing for the first time orthogonal multiple access. VLC-based indoor access system is also suitable for indoor localization due to its unique properties, such as utilization of existing ubiquitous lighting infrastructure, high location and orientation accuracy, and no interruption to RF-based devices. A novel retroreflector-based visible light localization system is proposed and prototyped to establish an almost zero-delay backward channel using a retroreflector to reflect light back to its source. This system can localize passive IoT devices without requiring computation and heavy sensing (e.g., camera) at the device end

Mechanism Design Theory in Control Engineering: A Tutorial and Overview of Applications in Communication, Power Grid, Transportation, and Security Systems

This article provides an introduction to the theory of mechanism design and its application to engineering problems. Our aim is to provide the fundamental principles of the theory of mechanism design for control engineers and theorists along with the state-of-the-art methods in engineering applications. We start our exposition with a brief overview of game theory highlighting the key notions that are necessary to introduce mechanism design, and then we offer a comprehensive discussion of the principles in mechanism design. Finally, we explore four key applications of mechanism design in engineering, i.e., communication networks, power grids, transportation, and security systems