Faster Information Dissemination in Dynamic Networks via Network Coding
Bernhard Haeupler, David Karger

TL;DR
This paper introduces a network coding approach to significantly accelerate information dissemination in dynamic networks, surpassing previous lower bounds and enabling faster broadcast times especially with larger message sizes.
Contribution
It demonstrates how network coding can break existing lower bounds for information dissemination in dynamic networks, leading to faster algorithms and deterministic solutions.
Findings
Network coding reduces broadcast rounds from quadratic to near-linear in message size.
Algorithms achieve T^2 speedup in networks changing every T rounds.
Deterministic algorithms derived from randomized network coding.
Abstract
We use network coding to improve the speed of distributed computation in the dynamic network model of Kuhn, Lynch and Oshman [STOC '10]. In this model an adversary adaptively chooses a new network topology in every round, making even basic distributed computations challenging. Kuhn et al. show that n nodes, each starting with a d-bit token, can broadcast them to all nodes in time O(n^2) using b-bit messages, where b > d + log n. Their algorithms take the natural approach of {token forwarding}: in every round each node broadcasts some particular token it knows. They prove matching Omega(n^2) lower bounds for a natural class of token forwarding algorithms and an Omega(n log n) lower bound that applies to all token-forwarding algorithms. We use network coding, transmitting random linear combinations of tokens, to break both lower bounds. Our algorithm's performance is quadratic in the…
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Taxonomy
TopicsCooperative Communication and Network Coding · Mobile Ad Hoc Networks · Wireless Communication Security Techniques
