Transfer^ encia de Dados entre Grupos de Processos no Modelo BAR

Peer-to-peer networks have emerged as a relevant architecture for executing scientific computations using resources provided by volunteers. However, this architecture poses several challenges, since volunteers may fail arbitrarily (Byzantine behaviour) or even follow a selfish behaviour (Rational behaviour), as indicated by the Byzantine-Altruistic-Rational (BAR) model. Also, if such distributed computations are to be performed in a computational model such as MapReduce, there must be some mechanism for reliably transferring data among tasks. This thesis introduces the N-party BAR Transfer (NBART) problem, which is the problem of reliably transferring data from a set of producers to a set of consumers, in the BAR model. This is an important building block for volunteer computing, since it allows tasks to reliably communicate among each other, and volunteers are not obliged to store the data for long periods of time. Instead, each volunteer may transfer the data, after storing it for a minimum amount of time, to another volunteer. This thesis also proposes two alternative algorithms for solving the NBART problem. One executes in a constant number of rounds and has greater communication complexity, while the other has a lower communication complexity but it has a greater execution time. It is proved that, if no volunteer follows a Rational behaviour, then both algorithms ensure a reliable transfer of data when a majority of producers and a majority of consumers are non-Byzantine. In addition, a theoretical analysis based on Game Theory is performed, proving that both algorithms provide a Nash equilibrium. Palavras Chave Keywords