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.
A multi-layer framework for graph processing via overlay composition
Dazzi P;Carlini E
2015
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.File | Dimensione | Formato | |
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