DocumentCode
1289924
Title
Optimizing Sensing: From Water to the Web
Author
Krause, Andreas ; Guestrin, Carlos
Author_Institution
Div. of Eng. & Appl. Sci., California Inst. of Technol., Pasadena, CA, USA
Volume
42
Issue
8
fYear
2009
Firstpage
38
Lastpage
45
Abstract
Where should we place sensors to quickly detect contamination in drinking water distribution networks? Which blogs should we read to learn about the biggest stories on the Web? Such problems are typically NP-hard in theory and extremely challenging in practice. The authors present algorithms that exploit submodularity to efficiently find provably near-optimal solutions to large complex real-world sensing problems.
Keywords
Internet; sensors; water pollution control; water pollution measurement; water supply; NP-hard problem; Web blogs; World Wide Web; drinking water contamination detection; drinking water distribution networks; large complex real-world sensing problems; water sensing; Algorithm design and analysis; Contamination; Cost function; Drilling; Equations; Greedy algorithms; Iterative algorithms; Pollution measurement; Protection; Water pollution; Active learning; Blogs; Environmental monitoring; Information gathering; Information overload; Observation selection; Submodular functions;
fLanguage
English
Journal_Title
Computer
Publisher
ieee
ISSN
0018-9162
Type
jour
DOI
10.1109/MC.2009.265
Filename
5197423
Link To Document