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Kadcast: A Structured Approach to Broadcast in Blockchain Networks

Published: 21 October 2019 Publication History

Abstract

In order to propagate transactions and blocks, today's blockchain systems rely on unstructured peer-to-peer overlay networks. In such networks, broadcast is known to be an inefficient operation in terms of message complexity and overhead. In addition to the impact on the system performance, inefficient or delayed block propagation may have severe consequences regarding security and fairness of the consensus layer. Therefore, we introduce Kadcast, a novel peer-to-peer protocol for block propagation in blockchain networks. Kadcast utilizes the well-known structured overlay topology of Kademlia to realize an efficient broadcast operation with tunable overhead. As our protocol is based on UDP, we incorporate forward error correction (FEC) to increase reliability while still maintaining its lightweight protocol architecture. To this end, we build a probabilistic model to analyze Kadcast's resilience to packet losses and node failures. Moreover, we evaluate Kadcast's block delivery performance, broadcast reliability, efficiency, and security based on advanced network simulations, which confirm the merits of the Kadcast protocol.

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cover image ACM Conferences
AFT '19: Proceedings of the 1st ACM Conference on Advances in Financial Technologies
October 2019
240 pages
ISBN:9781450367325
DOI:10.1145/3318041
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 21 October 2019

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