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M. J. Taylor

dblp:58/5639 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Artificial intelligence
1 paper
Probabilistic and Bayesian machine learning · 100%
Computer networks
1 paper
Cellular and mobile networks · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems › replication › replica consistency
replica synchronization
0.012001
Optimising Synchronisation Times for Mobile Devices · NIPS 2001
Distributed systems
replication
0.012001
Optimising Synchronisation Times for Mobile Devices · NIPS 2001

Methods — techniques the papers use, named apart from their topics

probabilistic modeling · 0.1objective function minimization · 0.1
YearPublicationVenuePosition
2001 Optimising Synchronisation Times for Mobile Devices
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 exam(cid:173) ple news databases, calendars and e-mail. ill 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 synchronisa(cid:173) tion timings. We demonstrate, using two real world data-sets, that a user can obtain more up-to-date information using our approach.
Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, M. J. Taylor
NIPS4