Controlled Matching Game for Resource Allocation and User Association in WLANs

In multi-rate IEEE 802.11 WLANs, the traditional user association based on the strongest received signal and the well known anomaly of the MAC protocol can lead to overloaded Access Points (APs), and poor or heterogeneous performance. Our goal is to propose an alternative game-theoretic approach for association. We model the joint resource allocation and user association as a matching game with complementarities and peer effects consisting of selfish players solely interested in their individual throughputs. Using recent game-theoretic results we first show that various resource sharing protocols actually fall in the scope of the set of stability-inducing resource allocation schemes. The game makes an extensive use of the Nash bargaining and some of its related properties that allow to control the incentives of the players. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as its MAC anomaly. The mechanism can be implemented as a virtual connectivity management layer to achieve efficient APs-user associations without modification of the MAC layer

Randomness and Fairness in Two-Sided Matching with Limited Interviews

We study the outcome in a matching market where both sides have limited ability to consider options. For example, in the national residency matching program, doctors are limited to apply to a small set of hospitals, and hospitals are limited by the time required to interview candidates. Our main findings are the following: (1) In markets where jobs can only consider a limited number of candidates for interview, it increases the size of the resulting matching if the system has a limit on the number of applications a candidate can send. (2) The fair system of all applicants being allowed to apply to the exact same number of positions maximizes the expected size of the matching. More particularly, starting from an integer k as the number of applications, the matching size decreases as a few applicants are allowed to apply to one additional position (and then increases again as they are all allowed to apply to k+1). Although it seems natural to expect that the size of the matching would be a monotone increasing and concave function in the number of applications, our results show that neither is true. These results hold even in a market where a-priori all jobs and all candidates are equally likely to be good, and the judgments of different employers and candidates are independent. Our main technical contribution is computing the expected size of the matching found via the deferred acceptance algorithm as a function of the number of interviews and applications in a market where preferences are uniform and independent. Through simulations we confirm that these findings extend to markets where rankings become correlated after the interviews

Tiered Random Matching Markets: Rank Is Proportional to Popularity

We study the stable marriage problem in two-sided markets with randomly generated preferences. Agents on each side of the market are divided into a constant number of "soft" tiers, which capture agents\u27 qualities. Specifically, every agent within a tier has the same public score, and agents on each side have preferences independently generated proportionally to the public scores of the other side. We compute the expected average rank which agents in each tier have for their partners in the man-optimal stable matching, and prove concentration results for the average rank in asymptotically large markets. Furthermore, despite having a significant effect on ranks, public scores do not strongly influence the probability of an agent matching to a given tier of the other side. This generalizes the results by Pittel [Pittel, 1989], which analyzed markets with uniform preferences. The results quantitatively demonstrate the effect of competition due to the heterogeneous attractiveness of agents in the market

Essays on Market Design

“Market Design […] strives to understand how the design of marketplaces influences the functioning of markets” (Roth 2018, p. 1609). The simple but powerful rationale of market design is to improve markets by actively designing them, guided by economic theory, empirical data, and carefully designed economic experiments. In recent years, economists have been successful in designing a variety of institutions, including spectrum auctions, electricity markets, feedback systems, kidney exchanges, and school choice (Chen et al., 2020). This thesis consists of four chapters, all devoted to different aspects and areas of market design. Another unifying element of this thesis is the methodology. In all chapters, laboratory experiments are conducted, data are analyzed, and the results are linked to real-world applications. Laboratory experimental studies are a particularly useful tool in the context of market design. They are often compared to a wind tunnel, where the performance of existing designs is studied in a simplified environment or even new design ideas are tested in a controlled environment (Chen et al., 2020). The first chapter looks at auction design. We investigate the puzzle behind the popularity of a non-binding soft reserve price in practice. Here, we use the laboratory as a "wind tunnel" to compare the performance of different existing auction designs in a controlled environment. Chapter two focuses on the design of feedback systems. In this chapter, we propose a small but very effective modification to existing feedback withdrawal mechanisms. Therefore, we use the possibility of laboratory experiments to test a new design idea that has not yet been implemented in practice and for which, of course, no field data are available. The third chapter is concerned with the area of school choice. Here, I investigate the value of fairness to participants in school choice markets, which can guide a market designer in choosing an appropriate algorithm. A laboratory experiment allows for the observation and control of student preferences that are typically unobservable in field data. Finally, chapter four focuses on norm information acquisition. When designing real-world institutions, incentives must be aligned with behavior in terms of underlying goals (Bolton and Ockenfels 2012). Therefore, social norms, which are known to be a powerful force influencing behavior, are of great importance for market design. We study how economic agents choose between different types of norm information in a social choice context with uncertainty

Controlled Matching Game for User Association and Resource Allocation in Multi-Rate WLANs

International audience—The deployment of IEEE 802.11 based WLANs in populated areas is such that many mobile terminals are covered by several Access Points (APs). These mobiles have the possibility to associate to the AP with the strongest signal (best-RSSI association scheme).This can lead to poor performances and overloaded APs. Moreover, the well known anomaly in the protocol at the MAC layer may also lead to very unpredictable performances and affect the system throughput due to the presence of heterogeneous data rate nodes and the shared nature of the 802.11 medium. The goal of this paper is to propose an alternative approach for the association. We model the joint resource allocation and mobile user association as a matching game with complementarities, peer effects and selfish players 1. We focus on the throughput fairness allocation induced by the saturated regime with equal packet sizes. We propose a novel three-stages mechanism for the modeling and control of load balancing, resource allocation and user association. We show that the proposed mechanism can greatly improve the efficiency of 802.11 with heterogeneous nodes and reduce the negative impact of peer effects such as the anomaly in IEEE 802.11

Essays in Applied Microeconomic Theory:

Thesis advisor: Uzi SegalThis collection of papers examines applications of microeconomic theory to practical problems. More specifically, I identify frictions between theoretical results and agent behavior. I seek to resolve these tensions by either proposing mechanisms to more closely capture the theoretical environment of interest or extending the model to more closely approximate the world as individuals perceive it. In the first chapter, "Compensation without Distortion,'' I propose a new mechanism for compensating subjects in preference elicitation experiments. The motivation for this tool is the theoretical problem of incentive compatibility in decision experiments. A hallmark of experimental economics is the connection between a subject's payment with their actions or decisions, however previous literature has highlighted shortcomings in this link between compensation and methods currently used to elicit beliefs. Specifically, compensating individuals based on choices they make increases reliability, however these payments can themselves distort subjects' preferences, limiting the resulting data's usefulness. I reexamine the source of the underlying theoretical tension, and propose using a stochastic termination mechanism called the "random stopping procedure'' (RSP). I show that the RSP is theoretically able to structurally avoid preference distortions induced by the current state of the art protocols. Changing the underlying context subjects answer questions—by resolving payoff uncertainty immediately after every decision is made—the assumed impossibility of asking multiple questions without creating preference distortions is theoretically resolved. To test this prediction, I conduct an experiment explicitly designed to test the accuracy of data gathered by the RSP against the current best practice for measuring subject preferences. Results show that RSP-elicited preferences more closely match a control group's responses than the alternative. In the second chapter, "School Choice and Class Size Externalities,'' I revisit the many-to-one matching problem of school choice. I focus on the importance of problem definition, and argue that the "standard'' school choice model is insufficiently sensitive to relevant characteristics of student preferences. Motivated by the observation that students care about both the school they attend, and how over- or under-crowded the school is, I extend the problem definition to allow students to report preferences over both schools and cohort sizes. (Cohort size is intended as a generalization of school crowding, relative resources, or other similar school characteristics.) I show that, if students do have preferences over schools and cohort sizes, current mechanisms lose many of their advantageous properties, and are no longer stable, fair, nor non-wasteful. Moreover, I show that current mechanisms no longer necessarily incentivize students to truthfully report their preferences over school orderings. Motivated by the observation that students care about both the school they attend, and how over- or under-crowded the school is, in "School Choice and Class Size Externalities'' I extend the standard school choice problem to incorporate both of these elements. I show that, if students do have preferences over schools and cohort sizes, current mechanisms are no longer stable, fair, nor non-wasteful. In response, I construct an alternative matching mechanism, called the deferred acceptance with voluntary withdrawals (DAwVW) mechanism, which improves on the underlying (unobserved) manipulability of "standard" mechanisms. The DAwVW mechanism is deterministic and terminates, more closely satisfies core desirable matching properties, and can yield substantial efficiency gains compared to mechanisms that do not consider class size. In the third chapter, I provide an overview of the history of decision experiments in economics, describe several of the underlying tensions that motivate my other projects, and identify alternative potential solutions that have been proposed by others to these problems. In this project, I add context to the larger field of experimental economics in which my research is situated. In addition to the mechanisms discussed by prior literature reviews, I incorporate and discuss recently developed payment and elicitation methods, and identify these new approaches' advantages and drawbacks.Thesis (PhD) — Boston College, 2022.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Economics

The Unfolding Tendency in the Federal Relationship to Private Accreditation in Higher Education

The government has come to rely on private organizations for accreditation in higher education. It created the Higher Education Amendments of 1992 Act, which provided for state postsecondary review entities to contract with the Department of Education

Optimization in Strategic Environments

This work considers the problem faced by a decision maker (planner) trying to optimize over incomplete data. The missing data is privately held by agents whose objectives are dierent from the planner's, and who can falsely report it in order to advance their objectives. The goal is to design optimization mechanisms (algorithms) that achieve "good" results when agents' reports follow a game-theoretic equilibrium. In the first part of this work, the goal is to design mechanisms that provide a small worst-case approximation ratio (guarantee a large fraction of the optimal value in all instances) at equilibrium. The emphasis is on strategyproof mechanisms|where truthfulness is a dominant strategy equilibrium|and on the approximation ratio at that equilibrium. Two problems are considered|variants of knapsack and facility location problems. In the knapsack problem, items are privately owned by agents, who can hide items or report fake ones; each agent's utility equals the total value of their own items included in the knapsack, while the planner wishes to choose the items that maximize the sum of utilities. In the facility location problem, agents have private linear single sinked/peaked preferences regarding the location of a facility on an interval, while the planner wishes to locate the facility in a way that maximizes one of several objectives. A variety of mechanisms and lower bounds are provided for these problems. The second part of this work explores the problem of reassigning students to schools. Students have privately known preferences over the schools. After an initial assignment is made, the students' preferences change, get reported again, and a reassignment must be obtained. The goal is to design a reassignment mechanism that incentivizes truthfulness, provides high student welfare, transfers relatively few students from their initial assignment, and respects student priorities at schools. The class of mechanisms considered is permuted lottery deferred acceptance (PLDA) mechanisms, which is a natural class of mechanisms based on permuting the lottery numbers students initially draw to decide the initial assignment. Both theoretical and experimental evidence is provided to support the use of a PLDA mechanism called reversed lottery deferred acceptance (RLDA). The evidence suggests that under some conditions, all PLDA mechanisms generate roughly equal welfare, and that RLDA minimizes transfers among PLDA mechanisms

Everyone Likes to Be Liked: Experimental Evidence from Matching Markets

Matching markets can be unstable when individuals prefer to be matched to a partner who also wants to be matched with them. Through a pre-registered and theory-guided laboratory experiment, we provide evidence that such reciprocal preferences exist, significantly decrease stability in matching markets, and are driven both by belief-based and preference-based motives. Participants expect partners who want to be matched with them to be more cooperative, and are more altruistic themselves. This leads to higher cooperation and larger profits when participants can consider each other's preferences