Optimising Synchronisation Times for Mobile Devices

Neil D. Lawrence, Anthony I. T. Rowstron, Christopher M. Bishop, Michael J. Taylor
,  14:1401-1408, 2002.

Abstract

With the increasing number of users of mobile computing devices (e.g. personal digital assistants) and the advent of third generation mobile phones, wireless communications are becoming increasingly important. Many applications rely on the device maintaining a *replica* of a data-structure which is stored on a server, for example news databases, calendars and e-mail. In this paper we explore the question of the optimal strategy for synchronising such replicas. We utilise probabilistic models to represent how the data-structures evolve and to model user behaviour. We then formulate objective functions which can be minimised with respect to the synchronisation timings. We demonstrate, using two real world data-sets, that a user can obtain more up-to-date information using our approach.

Cite this Paper


BibTeX
@InProceedings{pmlr-v-lawrence-sync01, title = {Optimising Synchronisation Times for Mobile Devices}, author = {Neil D. Lawrence and Anthony I. T. Rowstron and Christopher M. Bishop and Michael J. Taylor}, pages = {1401--1408}, year = {}, editor = {}, volume = {14}, address = {Cambridge, MA}, url = {http://inverseprobability.com/publications/lawrence-sync01.html}, abstract = {With the increasing number of users of mobile computing devices (e.g. personal digital assistants) and the advent of third generation mobile phones, wireless communications are becoming increasingly important. Many applications rely on the device maintaining a *replica* of a data-structure which is stored on a server, for example news databases, calendars and e-mail. In this paper we explore the question of the optimal strategy for synchronising such replicas. We utilise probabilistic models to represent how the data-structures evolve and to model user behaviour. We then formulate objective functions which can be minimised with respect to the synchronisation timings. We demonstrate, using two real world data-sets, that a user can obtain more up-to-date information using our approach.} }
Endnote
%0 Conference Paper %T Optimising Synchronisation Times for Mobile Devices %A Neil D. Lawrence %A Anthony I. T. Rowstron %A Christopher M. Bishop %A Michael J. Taylor %B %C Proceedings of Machine Learning Research %D %E %F pmlr-v-lawrence-sync01 %I PMLR %J Proceedings of Machine Learning Research %P 1401--1408 %U http://inverseprobability.com %V %W PMLR %X With the increasing number of users of mobile computing devices (e.g. personal digital assistants) and the advent of third generation mobile phones, wireless communications are becoming increasingly important. Many applications rely on the device maintaining a *replica* of a data-structure which is stored on a server, for example news databases, calendars and e-mail. In this paper we explore the question of the optimal strategy for synchronising such replicas. We utilise probabilistic models to represent how the data-structures evolve and to model user behaviour. We then formulate objective functions which can be minimised with respect to the synchronisation timings. We demonstrate, using two real world data-sets, that a user can obtain more up-to-date information using our approach.
RIS
TY - CPAPER TI - Optimising Synchronisation Times for Mobile Devices AU - Neil D. Lawrence AU - Anthony I. T. Rowstron AU - Christopher M. Bishop AU - Michael J. Taylor BT - PY - DA - ED - ID - pmlr-v-lawrence-sync01 PB - PMLR SP - 1401 DP - PMLR EP - 1408 L1 - UR - http://inverseprobability.com/publications/lawrence-sync01.html AB - With the increasing number of users of mobile computing devices (e.g. personal digital assistants) and the advent of third generation mobile phones, wireless communications are becoming increasingly important. Many applications rely on the device maintaining a *replica* of a data-structure which is stored on a server, for example news databases, calendars and e-mail. In this paper we explore the question of the optimal strategy for synchronising such replicas. We utilise probabilistic models to represent how the data-structures evolve and to model user behaviour. We then formulate objective functions which can be minimised with respect to the synchronisation timings. We demonstrate, using two real world data-sets, that a user can obtain more up-to-date information using our approach. ER -
APA
Lawrence, N.D., Rowstron, A.I.T., Bishop, C.M. & Taylor, M.J.. (). Optimising Synchronisation Times for Mobile Devices. , in PMLR :1401-1408

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