Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/37700

TitleAutonomous multi-dimensional slicing for large-scale distributed systems
Author(s)Pasquet, Mathieu
Maia, Francisco António Ferraz Martins Almeida
Rivière, Étienne
Schiavoni, Valerio
KeywordsSlicing
Self-organization
Skyline
Gossip-based protocols
Issue date2014
PublisherSpringer-Verlag Berlin
JournalLecture Notes in Computer Science
CitationPasquet M, Maia F, Rivière E, Schiavoni V. 2014. Autonomous Multi-Dimensional Slicing for Large-Scale Distributed Systems. Proceedings of the 14th International Conference on Distributed Applications and Interoperable Systems - DAIS.
Abstract(s)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.
TypeConference paper
URIhttp://hdl.handle.net/1822/37700
ISBN9783662433515
DOI10.1007/978-3-662-43352-2_12
ISSN0302-9743
Peer-Reviewedyes
AccessOpen access
Appears in Collections:HASLab - Artigos em atas de conferências internacionais (texto completo)

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