The problem of sharing the cost of multicast transmissions was studied in the past, and two mechanisms, marginal cost (MC) and Shapley value (SH), were proposed to solve it. Although both of them are strategy proof mechanisms, the distributed protocols implementing them are susceptible to manipulation by autonomous nodes. We propose a distributed Shapley value mechanism in which the participating nodes do not have incentives to deviate from the mechanism specifications. We show that the proposed mechanism is a faithful implementation of the Shapley value mechanism. We experimentally investigate the performance of the existing and the proposed cost-sharing mechanisms by implementing and deploying them on PlanetLab. We compare the execution time of MC and SH mechanisms for the tamper-proof and autonomous node models. We also study the convergence and scalability of the mechanisms by varying the number of nodes and the number of users per node. We show that the MC mechanisms generate a smaller revenue compared to the SH mechanisms, and thus, they are not attractive to the content provider. We also show that increasing the number of users per node is beneficial for the systems implementing the SH mechanisms from both computational and economic perspectives.

In this paper we investigate experimentally the performance of marginal cost (MC) and Shapley value (SH) mechanisms for sharing the cost of multicast transmissions. We implement and deploy the MC and SH mechanisms on PlanetLab and study their properties. We compare the execution time of MC and SH mechanisms for the tamper-proof and autonomous node models. We also study the convergence and scalability of the mechanisms by varying the number of nodes and the number of users per node. We show that the MC mechanisms generate a smaller revenue compared to the SH mechanisms and thus they are not favorable for the content provider. From the computational point of view as well as economic considerations, increasing the number of users per node is beneficial for the system implementing these mechanisms.

Sharing the cost of multicast transmissions was studied in the past and two mechanisms, Marginal Cost and Shapley Value, were proposed. Compared to the Marginal Cost Mechanism the Shapley Value mechanism has the advantage of being budget balanced. Although both of them are strategyproof mechanisms, the distributed protocols implementing them are susceptible to manipulation by autonomous nodes. We propose two protocols that implement the Shapley Value mechanism in which the nodes do not have incentives to deviate from the protocol specifications. We show that the proposed protocols are faithful implementations of the Shapley Value mechanism. We deploy these protocols on PlanetLab and analyze their performance.

Truthful task scheduling mechanisms are designed to cope with the selfishness of the participating agents. They assume that the agents are selfish; each agent's goal is to maximize its own profit. However, this is not always the case; an agent may want to cause losses to the other agents besides maximizing its profit. Such an agent is said to be an antisocial agent. An antisocial agent will try to gain as much profit as possible relative to the other agents. This paper presents an antisocial strategy which can be used by the antisocial agents to inflict losses on the other agents participating in a task scheduling mechanism on related machines. This paper also studies, by simulation, the effect of different parameters, such as the degree of antisociality on the relative losses that can be inflicted on the participating agents.