DocumentCode
3526553
Title
Neighborhood gossip: Concurrent averaging through local interference
Author
Nazer, Bobak ; Dimakis, Alexandros G. ; Gastpar, Michael
Author_Institution
Univ. of California, Berkeley, CA
fYear
2009
fDate
19-24 April 2009
Firstpage
3657
Lastpage
3660
Abstract
In this paper, we study a gossip algorithm for distributed averaging over a wireless sensor network. The usual assumption is that, through properly chosen codes, the physical layer is reduced to a set of reliable bit pipes for the distributed averaging algorithm. However, with a new channel coding technique, computation coding, we can exploit the interference property of the wireless medium for efficient averaging. This then provides a new abstraction for the physical layer: reliable linear equations instead of reliable bit pipes. The ldquoneighborhood gossiprdquo algorithm operates modularly on top of this abstraction. We will show that for certain regimes, such an approach can lead to energy savings that are exponential in the network size and time savings that are polynomial.
Keywords
channel coding; concurrency theory; distributed algorithms; linear codes; radiofrequency interference; telecommunication network reliability; wireless channels; wireless sensor networks; channel coding; computation coding; concurrent averaging algorithm; distributed averaging algorithm; local interference; neighborhood gossip algorithm; reliable bit pipe; reliable linear equation; wireless sensor network; Channel coding; Convergence; Equations; Interference; Linear code; Physical layer; Polynomials; Signal processing algorithms; Telecommunication network reliability; Wireless sensor networks; Distributed algorithms; distributed estimation; linear codes;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4960419
Filename
4960419
Link To Document