Abstract
In this paper we present a genetic self-stabilization protocol for the canonical distributed problem of leader election. A self-stabilizing distributed system is one that can be started in any global state, and, during its execution, will eventually reach a legitimate global state(s) and henceforth remain there, maintaining its integrity without any kind of outside intervention. Current self-stabilizing systems either program the stabilizing feature into their protocols, or they use randomized protocols and special processors to stabilize the system. We believe that self-stabilization should be an emergent property of a distributed system, and, by transforming a distributed problem to a model of evolution, which is inherently self-stabilizing, we demonstrate how the emergence of self-stabilization can be achieved. We attempt to achieve more than just solving a problem with a distributed genetic algorithm: we take a distributed problem and show how analogies from evolution can be used to solve it.
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Deugo, D., Oppacher, F. (1993). Achieving Self-Stabilization in a Distributed System Using Evolutionary Strategies. In: Albrecht, R.F., Reeves, C.R., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7533-0_58
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DOI: https://doi.org/10.1007/978-3-7091-7533-0_58
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82459-7
Online ISBN: 978-3-7091-7533-0
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