Probabilistic Modelling of Replica Divergence

Anthony I. T. Rowstron, Neil D. LawrenceChristopher M. Bishop
, 2001.

Abstract

It is common in distributed systems to replicate data. In many cases this data evolves in a consistent fashion and this evolution can be modelled. A *probabilistic model* of the evolution allows us to estimate the divergence of the replicas and can be used by the application to alter its behaviour, for example to control synchronisation times, to determine the propagation of writes, and to convey to the user information about how much the data may have evolved. In this paper, we describe how the evolution of the data may be modelled and outline how the probabilistic model may be utilised in various applications, concentrating on a news database example.

Cite this Paper


BibTeX
@InProceedings{pmlr-v-rowstron-sync01, title = {Probabilistic Modelling of Replica Divergence}, author = {Anthony I. T. Rowstron and Neil D. Lawrence and Christopher M. Bishop}, year = {}, editor = {}, url = {http://inverseprobability.com/publications/rowstron-sync01.html}, abstract = {It is common in distributed systems to replicate data. In many cases this data evolves in a consistent fashion and this evolution can be modelled. A *probabilistic model* of the evolution allows us to estimate the divergence of the replicas and can be used by the application to alter its behaviour, for example to control synchronisation times, to determine the propagation of writes, and to convey to the user information about how much the data may have evolved. In this paper, we describe how the evolution of the data may be modelled and outline how the probabilistic model may be utilised in various applications, concentrating on a news database example.} }
Endnote
%0 Conference Paper %T Probabilistic Modelling of Replica Divergence %A Anthony I. T. Rowstron %A Neil D. Lawrence %A Christopher M. Bishop %B %C Proceedings of Machine Learning Research %D %E %F pmlr-v-rowstron-sync01 %I PMLR %J Proceedings of Machine Learning Research %P -- %U http://inverseprobability.com %V %W PMLR %X It is common in distributed systems to replicate data. In many cases this data evolves in a consistent fashion and this evolution can be modelled. A *probabilistic model* of the evolution allows us to estimate the divergence of the replicas and can be used by the application to alter its behaviour, for example to control synchronisation times, to determine the propagation of writes, and to convey to the user information about how much the data may have evolved. In this paper, we describe how the evolution of the data may be modelled and outline how the probabilistic model may be utilised in various applications, concentrating on a news database example.
RIS
TY - CPAPER TI - Probabilistic Modelling of Replica Divergence AU - Anthony I. T. Rowstron AU - Neil D. Lawrence AU - Christopher M. Bishop BT - PY - DA - ED - ID - pmlr-v-rowstron-sync01 PB - PMLR SP - DP - PMLR EP - L1 - UR - http://inverseprobability.com/publications/rowstron-sync01.html AB - It is common in distributed systems to replicate data. In many cases this data evolves in a consistent fashion and this evolution can be modelled. A *probabilistic model* of the evolution allows us to estimate the divergence of the replicas and can be used by the application to alter its behaviour, for example to control synchronisation times, to determine the propagation of writes, and to convey to the user information about how much the data may have evolved. In this paper, we describe how the evolution of the data may be modelled and outline how the probabilistic model may be utilised in various applications, concentrating on a news database example. ER -
APA
Rowstron, A.I.T., Lawrence, N.D. & Bishop, C.M.. (). Probabilistic Modelling of Replica Divergence. , in PMLR :-

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