A two-stage multi-objective optimization of erasure coding in overlay networks

In the recent years, overlay networks have emergedas a crucial platform for deployment of various distributed applications. Many of these applications rely on data redundancy techniques, such as erasure coding, to achieve higher fault tolerance. However, erasure coding applied in large scale overlay networksentails various overheads in terms of storage, latency and datarebuilding costs. These overheads are largely attributed to theselected erasure coding scheme and the encoded chunk placementin the overlay network. This paper explores a multi-objective optimization approach for identifying appropriate erasure codingschemes and encoded chunk placement in overlay networks. Theuniqueness of our approach lies in the consideration of multipleerasure coding objectives such as encoding rate and redundancyfactor, with overlay network performance characteristics likestorage consumption, latency and system reliability. Our approach enables a variety of tradeoff solutions with respect tothese objectives to be identified in the form of a Pareto front. To solve this problem, we propose a novel two stage multi-objective evolutionary algorithm, where the first stage determinesthe optimal set of encoding schemes, while the second stageoptimizes placement of the corresponding encoded data chunksin overlay networks of varying sizes. We study the performanceof our method by generating and analyzing the Pareto optimalsets of tradeoff solutions. Experimental results demonstrate thatthe Pareto optimal set produced by our multi-objective approachincludes and even dominates the chunk placements delivered bya related state-of-The-Art weighted sum method.