A multi-layer framework for graph processing via overlay composition

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Abstract

The processing of graph in a parallel and distributed fashion is a constantly rising trend, due to the size of the today’s graphs. This paper proposes a multi-layer graph overlay approach to support the orchestration of distributed, vertex-centric computations targeting large graphs. Our approach takes inspiration from the overlay networks, a widely exploited approach for information dissemination, aggregation and computing orchestration in massively distributed systems. We propose Telos, an environment supporting the definition of multi-layer graph overlays which provides each vertex with a layered, vertex-centric, view of the graph. Telos is defined on the top of Apache Spark and has been evaluated by considering two well-known graph problems. We present a set of experimental results showing the effectiveness of our approach.

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APA

Lulli, A., Dazzi, P., Ricci, L., & Carlini, E. (2015). A multi-layer framework for graph processing via overlay composition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9523, pp. 515–527). Springer Verlag. https://doi.org/10.1007/978-3-319-27308-2_42

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