DocumentCode
3254687
Title
Probabilistic Analysis of Message Forwarding
Author
Moser, L.E. ; Melliar-Smith, P.M.
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
fYear
2013
fDate
July 30 2013-Aug. 2 2013
Firstpage
1
Lastpage
8
Abstract
In this paper, we present a novel algorithm that finds the probability density function for the number of distinct nodes reached, within a specific number of levels of message forwarding, for a fixed size network. The algorithm also finds the expected number of distinct nodes to which a message is forwarded, within a specific number of levels of message forwarding, as the sum of the number of nodes, weighted by the probability of reaching that number of nodes. In addition, the algorithm finds the probability density function for the number of distinct nodes at a given level of message forwarding, and the expected number of distinct nodes at that level. Using the algorithm, we calculate these probability density functions and expected values for various size networks, degrees of message forwarding, probabilities of message forwarding, and levels of message forwarding. The algorithm has application to the Internet, peer-to-peer networks, ad-hoc networks, and social networks, and to multicasting, gossiping, and rumor and epidemic protocols.
Keywords
Internet; ad hoc networks; multicast protocols; peer-to-peer computing; probability; social networking (online); Internet; ad-hoc networks; distinct nodes; epidemic protocols; fixed size network; gossiping protocols; message forwarding; multicasting protocols; peer-to-peer networks; probabilistic analysis; probability density function; rumor protocols; social networks; Ad hoc networks; Algorithm design and analysis; Multicast communication; Peer-to-peer computing; Probabilistic logic; Probability; Probability density function;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Communications and Networks (ICCCN), 2013 22nd International Conference on
Conference_Location
Nassau
Print_ISBN
978-1-4673-5774-6
Type
conf
DOI
10.1109/ICCCN.2013.6614173
Filename
6614173
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