Sciweavers
Explore
Publications
Books
Software
Tutorials
Presentations
Lectures Notes
Datasets
Labs
Conferences
Community
Upcoming
Conferences
Top Ranked Papers
Most Viewed Conferences
Conferences by Acronym
Conferences by Subject
Conferences by Year
Tools
Sci2ools
International Keyboard
Graphical Social Symbols
CSS3 Style Generator
OCR
Web Page to Image
Web Page to PDF
Merge PDF
Split PDF
Latex Equation Editor
Extract Images from PDF
Convert JPEG to PS
Convert Latex to Word
Convert Word to PDF
Image Converter
PDF Converter
Community
Sciweavers
About
Terms of Use
Privacy Policy
Cookies
Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools
19
click to vote
DSN
2009
IEEE
favorite
Email
discuss
report
107
views
Computer Networks
»
more
DSN 2009
»
Parametric NdRFT for the derivation of optimal repair strategies
14 years 3 months ago
Download
www.sti.uniurb.it
Marco Beccuti, Giuliana Franceschinis, Daniele Cod
Real-time Traffic
Computer Networks
|
DSN 2009
|
claim paper
Related Content
»
PeertoPeer Storage Systems A Practical Guideline to be Lazy
»
Optimal Maintenance Strategies for Wind Turbine Systems Under Stochastic Weather Condition...
»
Joint designtime and postsilicon minimization of parametric yield loss using adjustable ro...
»
Distributed Storage Codes Meet MultipleAccess Wiretap Channels
»
Optimal stopping for eventtriggered sensing and actuation
»
Discrete mixtures of kernels for Krigingbased optimization
»
Optimized space sampling for circular image cube trajectory analysis
»
Reinforcement Learning for Vulnerability Assessment in PeertoPeer Networks
»
A minimax approach to Bayesian estimation with partial knowledge of the observation model
more »
Post Info
More Details (n/a)
Added
20 May 2010
Updated
20 May 2010
Type
Conference
Year
2009
Where
DSN
Authors
Marco Beccuti, Giuliana Franceschinis, Daniele Codetta Raiteri, Serge Haddad
Comments
(0)
Researcher Info
Computer Networks Study Group
Computer Vision