Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/38951

TitleSlead: low-memory, steady distributed systems slicing
Author(s)Maia, Francisco António Ferraz Martins Almeida
Matos, Miguel
Rivière, Etienne
Oliveira, Rui Carlos Mendes de
Issue date2012
PublisherACM
JournalLecture Notes in Computer Science (including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract(s)Slicing a large-scale distributed system is the process of autonomously partitioning its nodes into k groups, named slices. Slicing is associated to an order on node-specific criteria, such as available storage, uptime, or bandwidth. Each slice corresponds to the nodes between two quantiles in a virtual ranking according to the criteria. For instance, a system can be split in three groups, one with nodes with the lowest uptimes, one with nodes with the highest uptimes, and one in the middle. Such a partitioning can be used by applications to assign different tasks to different groups of nodes, e.g., assigning critical tasks to the more powerful or stable nodes and less critical tasks to other slices. Assigning a slice to each node in a large-scale distributed system, where no global knowledge of nodes’ criteria exists, is not trivial. Recently, much research effort was dedicated to guaranteeing a fast and correct convergence in comparison to a global sort of the nodes. Unfortunately, state-of-the-art slicing protocols exhibit flaws that preclude their application in real scenarios, in particular with respect to cost and stability. In this paper, we identify steadiness issues where nodes in a slice border constantly exchange slice and large memory requirements for adequate convergence, and provide practical solutions for the two. Our solutions are generic and can be applied to two different state-of-the-art slicing protocols with little effort and while preserving the desirable properties of each. The effectiveness of the proposed solutions is extensively studied in several simulated experiments.
TypeConference paper
URIhttp://hdl.handle.net/1822/38951
ISBN978-3-642-30822-2
DOI10.1007/978-3-642-30823-9_1
ISSN0302-9743
Publisher versionhttp://dl.acm.org/citation.cfm?id=2366628
Peer-Reviewedyes
AccessOpen access
Appears in Collections:HASLab - Artigos em atas de conferências internacionais (texto completo)

Files in This Item:
File SizeFormat 
746.pdf353,87 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID