We examine the relation between the size of the id space and the number of rational agents in a network under which equilibrium in distributed algorithms is possible. When the number of agents in the network is not a-priori known, but the id space is limited, a single agent may duplicate to gain an advantage but each duplication involves a risk of being caught. Given an id space of size L, we provide a method of calculating the threshold, the minimal value t such that agents know that n ≥ t, such that the algorithm is in equilibrium. We apply the method to Leader Election and Knowledge Sharing, and provide a constant-time approximation t ≈ L / 5 of the threshold for Leader Election.
CITATION STYLE
Bank, D., Sulamy, M., & Waserman, E. (2018). Reaching distributed equilibrium with limited ID space. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11085, pp. 48–51). Springer Verlag. https://doi.org/10.1007/978-3-030-01325-7_9
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