Published December 9, 2014 | Version v1
Conference paper

Dealing with Skewed Data in Structured Overlays using Variable Hash Functions

Others:
Safe Composition of Autonomous applications with Large-SCALE Execution environment (SCALE) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-COMmunications, Réseaux, systèmes Embarqués et Distribués (Laboratoire I3S - COMRED) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
The University of Hong Kong

Description

Storing highly skewed data in a distributed system has become a very frequent issue, in particular with the emergence of semantic web and Big Data. This often leads to biased data dissemination among nodes. Addressing load imbalance is necessary, especially to minimize response time and avoid workload being handled by only one or few nodes. Our contribution aims at dynamically managing load imbalance by allowing multiple hash functions on different peers, while maintaining consistency of the overlay. Our experiments, on highly skewed data sets from the semantic web, show we can distribute data on at least 300 times more peers than when not using any load balancing strategy.

Abstract

International audience

Additional details

Created:
March 25, 2023
Modified:
November 27, 2023