### Analyzing Network Coding (Gossip) Made EasyAnalyzing Network Coding (Gossip) Made Easy

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 Author Haeupler, Bernhard Source ACM Digital Library Content type Text Publisher Association for Computing Machinery (ACM) File Format PDF Copyright Year ©2016 Language English
 Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science Subject Keyword Random linear network coding ♦ Dynamic networks ♦ Gossip ♦ Multicast Abstract We introduce projection analysis—a new technique to analyze the stopping time of protocols that are based on random linear network coding (RLNC). Projection analysis drastically simplifies, extends, and strengthens previous results on RLNC gossip protocols. We analyze RLNC gossip in a general framework for network and communication models that encompasses and unifies the models used previously in this context. We show, in most settings for the first time, that the RLNC gossip converges with high probability in optimal time. Most stopping times are of the form $\textit{O}(\textit{k}$ + $\textit{T}),$ where $\textit{k}$ is the number of messages to be distributed and $\textit{T}$ is the time it takes to disseminate one message. This means RLNC gossip achieves “perfect pipelining.” Our analysis directly extends to highly dynamic networks in which the topology can change completely at any time. This remains true, even if the network dynamics are controlled by a fully adaptive adversary that knows the complete network state. Virtually nothing besides simple $\textit{O}(\textit{kT})$ sequential flooding protocols was previously known for such a setting. While RLNC gossip works in this wide variety of networks our analysis remains the same and extremely simple. This contrasts with more complex proofs that were put forward to give less strong results for various special cases. ISSN 00045411 Age Range 18 to 22 years ♦ above 22 year Educational Use Research Education Level UG and PG Learning Resource Type Article Publisher Date 2016-08-01 Publisher Place New York e-ISSN 1557735X Journal Journal of the ACM (JACM) Volume Number 63 Issue Number 3 Page Count 22 Starting Page 1 Ending Page 22

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Source: ACM Digital Library