Abstract
We consider the problem of profit optimization for cloud brokerage service in the IaaS environment. We replace this optimization problem with a game-theoretic approach where players tend to achieve a solution by reaching a Nash equilibrium. We propose a fully distributed algorithm based on applying the Spatial Prisoner’s Dilemma (SPD) game and a phenomenon of collective behavior of players participating in the game composed of two classes of automata-based agents - Cellular Automata (CA) and Learning Automata (LA). We introduce dynamic strategies like local profit sharing, mutation, and competition, which stimulate the evolutionary process of developing collective behavior among players to maximize their profit margin. We present the results of an experimental study showing the emergence of collective behavior in such systems.
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Gąsior, J., Seredyński, F. (2022). A Distributed Game-Theoretic Approach to IaaS Cloud Brokering. In: Chaves, R., et al. Euro-Par 2021: Parallel Processing Workshops. Euro-Par 2021. Lecture Notes in Computer Science, vol 13098. Springer, Cham. https://doi.org/10.1007/978-3-031-06156-1_7
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