Abstract
This paper presents an optimization framework for finding efficient deployment mappings of replicated service components (to nodes), while accounting for multiple services simultaneously and adhering to non-functional requirements. Currently, we consider load-balancing and dependability requirements. Our approach is based on a variant of Ant Colony Optimization and is completely decentralized, where ants communicate indirectly through pheromone tables in nodes. In this paper, we target scalability; however, existing encoding schemes for the pheromone tables did not scale. Hence, we propose and evaluate three different pheromone encodings. Using the most scalable encoding, we evaluate our approach in a significantly larger system than our previous work. We also evaluate the approach in terms of robustness to network partition failures.
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Csorba, M.J., Meling, H., Heegaard, P.E. (2009). Laying Pheromone Trails for Balanced and Dependable Component Mappings. In: Spyropoulos, T., Hummel, K.A. (eds) Self-Organizing Systems. IWSOS 2009. Lecture Notes in Computer Science, vol 5918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10865-5_5
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DOI: https://doi.org/10.1007/978-3-642-10865-5_5
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