Autonomous Multi-dimensional Slicing for Large-Scale Distributed Systems

Abstract : Slicing is a distributed systems primitive that allows to autonomously partition a large set of nodes based on node-local attributes. Slicing is decisive for automatically provisioning system resources for different services, based on their requirements or importance. One of the main limitations of existing slicing protocols is that only single dimension attributes are considered for partitioning. In practical settings, it is often necessary to consider best compromises for an ensemble of metrics.In this paper we propose an extension of the slicing primitive that allows multi-attribute distributed systems slicing.Our protocol employs a gossip-based approach that does not require centralized knowledge and allows self-organization. It leverages the notion of domination between nodes, forming a partial order between multi-dimensional points, in a similar way to SkyLine queries for databases. We evaluate and demonstrate the interest of our approach using large-scale simulations.
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Mathieu Pasquet, Francisco Maia, Etienne Rivière, Valerio Schiavoni. Autonomous Multi-dimensional Slicing for Large-Scale Distributed Systems. 4th International Conference on Distributed Applications and Interoperable Systems (DAIS), Jun 2014, Berlin, Germany. pp.141-155, ⟨10.1007/978-3-662-43352-2_12⟩. ⟨hal-01287739⟩

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