Networked Information

Abstract—Swarm-inspired algorithms allow the creation of complex systems that are scalable in many dimensions, adapt-able to changing conditions, and robust against failure. These properties make them suitable for the challenges inherent in distributed storage systems. However, these swarm-based approaches reach their impressive performance by trading away correctness guarantees, occasionally leading to misplaced data items. In order to achieve consistent storage, there is a need for a constant optimization of the store’s data structure. In this paper, we describe a fully distributed and scalable heuristic for the optimization of the location of stored data items within a distributed storage system based on the brood sorting method used by ants. We evaluate our heuristic using best- and worst-case test data sets to determine whether our location optimization method converges and whether it improves the location and organization of data inside a large-scale storage network