Analyzing Network Coding Gossip Made Easy

Computer Science – Distributed – Parallel – and Cluster Computing

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

We give a new technique to analyze the stopping time of gossip protocols that are based on random linear network coding (RLNC). Our analysis drastically simplifies, extends and strengthens previous results. 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 it converges with high probability in the information-theoretically optimal time. Most stopping times are of the form O(k + T) where k is the number of messages to be distributed and 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 O(kT) sequential flooding protocols was previously known for such a setting. While RLNC gossip works in this wide variety of networks its 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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Analyzing Network Coding Gossip Made Easy does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Analyzing Network Coding Gossip Made Easy, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Analyzing Network Coding Gossip Made Easy will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-274555

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.