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, a single agent may duplicate to gain an advantage, pretending to be more than one agent. However, when the id space is limited, each duplication involves a risk of being caught. By comparing the risk against the advantage, given an id space of size L, we provide a method of calculating the minimal threshold t, the required number of agents in the network, such that the algorithm is in equilibrium. That is, it is the minimal value of t such that if agents a-priori know that n ≥ t then the algorithm is in equilibrium. We demonstrate this method by applying it to two problems, Leader Election and Knowledge Sharing, as well as providing a constant-time approximation t ≈ L 5 of the minimal threshold for Leader Election.
In REF the authors remove this assumption and assume the id space is bounded, examining the relation between the size of the id space and the number of agents in the network in which an equilibrium is possible.
Reaching Distributed Equilibrium with Limited ID Space
ArXiv
ArXiv
Computer Science