Fair linking mechanisms for resource allocation with correlated player types

The proceeding at: Second International Conference,Networked Systems (NETYS 2014), took place 2014. May 15-17. in Marrakech, Morocco.Resource allocation is one of the most relevant problems in the area of Mechanism Design for computing systems. Devising algorithms capable of providing efficient and fair allocation is the objective of many previous research efforts. Usually, the mechanisms they propose use payments in order to deal with selfishness. Since using payments is undesirable in some contexts, a family of mechanisms without payments is proposed in this paper. These mechanisms extend the Linking Mechanism of Jackson and Sonnenschein introducing a generic concept of fairness with correlated preferences. We prove that these mechanisms have good incentive, fairness, and efficiency properties. To conclude, we provide an algorithm, based on the mechanisms, that could be used in practical computing environments.Publicad

Fair linking mechanisms for resource allocation with correlated player types

Resource allocation is one of the most relevant problems in the area of Mechanism Design for computing systems. Devising algorithms capable of providing efficient and fair allocation is the objective of many previous research efforts. Usually, the mechanisms they propose deal with selfishness by introducing utility transfers or payments. Since using payments is undesirable in some contexts, a family of mechanisms without payments is proposed in this paper. These mechanisms extend the Linking Mechanism of Jackson and Sonnenschein introducing a generic concept of fairness with correlated preferences. We prove that these mechanisms have good incentive, fairness, and efficiency properties. To conclude, we provide an algorithm, based on the mechanisms, that could be used in practical computing environments.Publicad

A Mechanism for Fair Distribution of Resources without Payments

We design a mechanism for Fair and Efficient Distribution of Resources (FEDoR) in the presence of strategic agents. We consider a multiple-instances, Bayesian setting, where in each round the preference of an agent over the set of resources is a private information. We assume that in each of r rounds n agents are competing for k non-identical indivisible goods, (n > k). In each round the strategic agents declare how much they value receiving any of the goods in the specific round. The agent declaring the highest valuation receives the good with the highest value, the agent with the second highest valuation receives the second highest valued good, etc. Hence we assume a decision function that assigns goods to agents based on their valuations. The novelty of the mechanism is that no payment scheme is required to achieve truthfulness in a setting with rational/strategic agents. The FEDoR mechanism takes advantage of the repeated nature of the framework, and through a statistical test is able to punish the misreporting agents and be fair, truthful, and socially efficient. FEDoR is fair in the sense that, in expectation over the course of the rounds, all agents will receive the same good the same amount of times. FEDoR is an eligible candidate for applications that require fair distribution of resources over time. For example, equal share of bandwidth for nodes through the same point of access. But further on, FEDoR can be applied in less trivial settings like sponsored search, where payment is necessary and can be given in the form of a flat participation fee. To this extent we perform a comparison with traditional mechanisms applied to sponsored search, presenting the advantage of FEDoR

A Fair and Scalable Mechanism for Resource Allocation: The Multilevel QPQ Approach

In this paper the problem of distributing resources among a collection of users (or players) is explored. These players have independent preferences to get these resources and can be dishonest about their preferences in order to increase their utility (their preference for the resources they are allocated). The objective is design a mechanism to allocate resources to players so that all of them get the same amount of resources (fair), the total utility is maximized (optimal), and no player has incentive to be dishonest (strategy proof). Santos et al. proposed the Quid Pro Quo (QPQ) mechanism to solve this problem. In this paper a generalization of the QPQ mechanism is proposed that, in addition to the above properties, has a very high degree of scalability. The proposed multilevel QPQ mechanism divides the players into disjoint clusters and runs a mechanism similar to QPQ inside each cluster and across selected players in each cluster. As a consequence the amount of communication required is drastically reduced. Similarly, the storage used by the mechanism by each player is also significantly reduced, which in a practical setting can be used to improve the ability to detect dishonest players.This work was supported in part by the Regional Government of Madrid (CM) grant EdgeData-CM (P2018/TCS4499) cofunded by the FSE & FEDER, in part by the NSF of China under Grant 61520106005, and in part by the Ministry of Science and Innovation Grant PID2019-109805RB-I00 (ECID) co-funded by the FEDER. The work of Josu Doncel was supported in part by the Department of Education of the Basque Government through the Consolidated Research Group MATH-MODE (IT1294-19), in part by the Marie Sklodowska-Curie Grant agreement No. 777778, and in part by the Spanish Ministry of Science and Innovation with reference PID2019-108111RB-I00 (FEDER/AEI)

Advances in negotiation theory : bargaining, coalitions, and fairness

Bargaining is ubiquitous in real life. It is a major dimension of political and business activities. It appears at the international level, when governments negotiate on matters ranging from economic issues (such as the removal of trade barriers), to global security (such as fighting against terrorism) to environmental and related issues (such as climate change control). What factors determinethe outcomes of such negotiations? What strategies can help reach an agreement? How should the parties involved divide the gains from cooperation? With whom will one make alliances? The authors address these questions by focusing on a noncooperative approach to negotiations, which is particularly relevant for the study of international negotiations. By reviewing noncooperative bargaining theory, noncooperative coalition theory, and the theory of fair division, they try to identify the connections among these different facets of the same problem in an attempt to facilitate progress toward a unified framework.Economic Theory&Research,Social Protections&Assistance,Environmental Economics&Policies,Scientific Research&Science Parks,Science Education

Advances in Negotiation Theory: Bargaining, Coalitions and Fairness

Bargaining is ubiquitous in real-life. It is a major dimension of political and business activities. It appears at the international level, when governments negotiate on matters ranging from economic issues (such as the removal of trade barriers), to global security (such as fighting against terrorism) to environmental and related issues (e.g. climate change control). What factors determine the outcome of negotiations such as those mentioned above? What strategies can help reach an agreement? How should the parties involved divide the gains from cooperation? With whom will one make alliances? This paper addresses these questions by focusing on a non-cooperative approach to negotiations, which is particularly relevant for the study of international negotiations. By reviewing noncooperative bargaining theory, non-cooperative coalition theory, and the theory of fair division, this paper will try to identify the connection among these different facets of the same problem in an attempt to facilitate the progress towards a unified framework.Negotiation theory, Bragaining, Coalitions, Fairness, Agreements

Advances in Negotiation Theory: Bargaining, Coalitions and Fairness

Bargaining is ubiquitous in real-life. It is a major dimension of political and business activities. It appears at the international level, when governments negotiate on matters ranging from economic issues (such as the removal of trade barriers), to global security (such as fighting against terrorism) to environmental and related issues (e.g. climate change control). What factors determine the outcome of negotiations such as those mentioned above? What strategies can help reach an agreement? How should the parties involved divide the gains from cooperation? With whom will one make alliances? This paper addresses these questions by focusing on a non-cooperative approach to negotiations, which is particularly relevant for the study of international negotiations. By reviewing non-cooperative bargaining theory, non-cooperative coalition theory, and the theory of fair division, this paper will try to identify the connection among these different facets of the same problem in an attempt to facilitate the progress towards a unified framework.Negotiation theory, Bargaining, Coalitions, Fairness, Agreements

Collusion in Peer-to-Peer Systems

Peer-to-peer systems have reached a widespread use, ranging from academic and industrial applications to home entertainment. The key advantage of this paradigm lies in its scalability and flexibility, consequences of the participants sharing their resources for the common welfare. Security in such systems is a desirable goal. For example, when mission-critical operations or bank transactions are involved, their effectiveness strongly depends on the perception that users have about the system dependability and trustworthiness. A major threat to the security of these systems is the phenomenon of collusion. Peers can be selfish colluders, when they try to fool the system to gain unfair advantages over other peers, or malicious, when their purpose is to subvert the system or disturb other users. The problem, however, has received so far only a marginal attention by the research community. While several solutions exist to counter attacks in peer-to-peer systems, very few of them are meant to directly counter colluders and their attacks. Reputation, micro-payments, and concepts of game theory are currently used as the main means to obtain fairness in the usage of the resources. Our goal is to provide an overview of the topic by examining the key issues involved. We measure the relevance of the problem in the current literature and the effectiveness of existing philosophies against it, to suggest fruitful directions in the further development of the field

Achieving reliability and fairness in online task computing environments

Mención Internacional en el título de doctorWe consider online task computing environments such as volunteer computing platforms running on BOINC (e.g., SETI@home) and crowdsourcing platforms such as Amazon Mechanical Turk. We model the computations as an Internet-based task computing system under the masterworker paradigm. A master entity sends tasks across the Internet, to worker entities willing to perform a computational task. Workers execute the tasks, and report back the results, completing the computational round. Unfortunately, workers are untrustworthy and might report an incorrect result. Thus, the first research question we answer in this work is how to design a reliable masterworker task computing system. We capture the workers’ behavior through two realistic models: (1) the “error probability model” which assumes the presence of altruistic workers willing to provide correct results and the presence of troll workers aiming at providing random incorrect results. Both types of workers suffer from an error probability altering their intended response. (2) The “rationality model” which assumes the presence of altruistic workers, always reporting a correct result, the presence of malicious workers always reporting an incorrect result, and the presence of rational workers following a strategy that will maximize their utility (benefit). The rational workers can choose among two strategies: either be honest and report a correct result, or cheat and report an incorrect result. Our two modeling assumptions on the workers’ behavior are supported by an experimental evaluation we have performed on Amazon Mechanical Turk. Given the error probability model, we evaluate two reliability techniques: (1) “voting” and (2) “auditing” in terms of task assignments required and time invested for computing correctly a set of tasks with high probability. Considering the rationality model, we take an evolutionary game theoretic approach and we design mechanisms that eventually achieve a reliable computational platform where the master receives the correct task result with probability one and with minimal auditing cost. The designed mechanisms provide incentives to the rational workers, reinforcing their strategy to a correct behavior, while they are complemented by four reputation schemes that cope with malice. Finally, we also design a mechanism that deals with unresponsive workers by keeping a reputation related to the workers’ response rate. The designed mechanism selects the most reliable and active workers in each computational round. Simulations, among other, depict the trade-off between the master’s cost and the time the system needs to reach a state where the master always receives the correct task result. The second research question we answer in this work concerns the fair and efficient distribution of workers among the masters over multiple computational rounds. Masters with similar tasks are competing for the same set of workers at each computational round. Workers must be assigned to the masters in a fair manner; when the master values a worker’s contribution the most. We consider that a master might have a strategic behavior, declaring a dishonest valuation on a worker in each round, in an attempt to increase its benefit. This strategic behavior from the side of the masters might lead to unfair and inefficient assignments of workers. Applying renown auction mechanisms to solve the problem at hand can be infeasible since monetary payments are required on the side of the masters. Hence, we present an alternative mechanism for fair and efficient distribution of the workers in the presence of strategic masters, without the use of monetary incentives. We show analytically that our designed mechanism guarantees fairness, is socially efficient, and is truthful. Simulations favourably compare our designed mechanism with two benchmark auction mechanisms.This work has been supported by IMDEA Networks Institute and the Spanish Ministry of Education grant FPU2013-03792.Programa Oficial de Doctorado en Ingeniería MatemáticaPresidente: Alberto Tarable.- Secretario: José Antonio Cuesta Ruiz.- Vocal: Juan Julián Merelo Guervó

Managing resources in erratic environments: an analysis of pastoralist systems in Ethiopia, Niger, and Burkina Faso

This study analyzes the links between risk and the kinds of property rights that have evolved to provide the mobility necessary to raise livestock in drought-prone countries in this case Burkina Faso, Ethiopia, and Niger. The study also evaluates the impact of cooperation on resource management in these environments. The express purpose of this research is to contribute to the current debate on resource management in highly variable environments, focusing on the impact of climate variability on and the role of cooperation in resource management. More specifically, a conceptual framework is developed to analyze the impact of climatic variability and cooperative capacity on land allocation patterns, stock densities, and patterns of herd mobility. Overall, the empirical results suggest that effective policies for sustainable land management and crisis-response plans may require the design and implementation of mechanisms to increase cooperative capacity.Range management Ethiopia, Range management Niger, Range management Burkina Faso, Pastoral systems,