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Automatic network configuration with dynamic churn prediction


Lareida, Andri; Bocek, Thomas; Pernebayev, Maxat; Stiller, Burkhard (2015). Automatic network configuration with dynamic churn prediction. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), Ottawa, Canada, 11 May 2015 - 15 May 2015. IEEE, 363-370.

Abstract

Peer-to-Peer (P2P) systems have been deployed on millions of nodes worldwide in environments that range from static to very dynamic and therefore exhibit different churn levels. Typically, P2P systems introduce redundancy to cope with loss of nodes. In distributed hash tables, redundancy often fixed during development or at initial deployment of the system. This can limit the applicability of the system to stable environments or make them inefficient in such environments. Automatic network configuration can make a system more adaptable to changing environments and reduce manual configuration tasks. Therefore, this paper proposes an automatic replication configuration based on churn prediction that automatically adapts its replication configuration to its environment. The mechanism termed dynamic replication mechanism (dynamic RM) developed and evaluated in this paper is based on exponential moving averages to predict churn that is used itself to determine a replication factor meeting a certain reliability threshold. Simulations with synthetic data and experiments with data from torrent trackers show that the behavior can be predicted accurately in any environment, from low churn rates to diurnal and high churn rates.

Abstract

Peer-to-Peer (P2P) systems have been deployed on millions of nodes worldwide in environments that range from static to very dynamic and therefore exhibit different churn levels. Typically, P2P systems introduce redundancy to cope with loss of nodes. In distributed hash tables, redundancy often fixed during development or at initial deployment of the system. This can limit the applicability of the system to stable environments or make them inefficient in such environments. Automatic network configuration can make a system more adaptable to changing environments and reduce manual configuration tasks. Therefore, this paper proposes an automatic replication configuration based on churn prediction that automatically adapts its replication configuration to its environment. The mechanism termed dynamic replication mechanism (dynamic RM) developed and evaluated in this paper is based on exponential moving averages to predict churn that is used itself to determine a replication factor meeting a certain reliability threshold. Simulations with synthetic data and experiments with data from torrent trackers show that the behavior can be predicted accurately in any environment, from low churn rates to diurnal and high churn rates.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Computer Science Applications
Physical Sciences > Computer Networks and Communications
Language:English
Event End Date:15 May 2015
Deposited On:18 Dec 2015 10:50
Last Modified:26 Jan 2022 07:31
Publisher:IEEE
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/INM.2015.7140312
Other Identification Number:merlin-id:12735
  • Content: Published Version
  • Description: Abstract