University of Illinois Urbana-Champaign

Barracuda: The power of l-polling in proof of stake blockchains

Rana, Ranvir

Content Files
RANA-THESIS-2020.pdf

Permalink

https://hdl.handle.net/2142/109389

Description

Title
Barracuda: The power of l-polling in proof of stake blockchains
Author(s)
Rana, Ranvir
Issue Date
2020-11-30
Director of Research (if dissertation) or Advisor (if thesis)
Viswanath, Pramod
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2021-03-05T21:38:06Z
Keyword(s)
  • Blockchain
  • Distributed, Parallel, and Cluster Computing
  • Cryptography and Security
  • Information Theory
Abstract
Blockchain is a database of storing sequential events as a chain of blocks consistently across a distributed set of nodes. A fundamental problem in doing so is to decide where to put the next block and who should do it in a Sybil-resistant manner. To solve this problem, typically, a node is elected randomly as a leader to append a new block to the end of a chain stored locally by the leader. Ideally, this should extend the chain of blocks, however in practice, due to network imperfections, the local blockchain of the leader might not be synced entirely, thus resulting in forking, a scenario when a new block is appended in the middle of the blockchain, thus creating a fork. These network imperfections create a structure like a tree rather than a chain, where blocks not part of the main chain are abandoned, thus reducing the system’s efficiency. We propose a new peer-to-peer (P2P) protocol called Barracuda, where the leader polls l − 1 random nodes for their blocktree information before proposing a new block and show that this policy has an effect equivalent to having a network that is l times faster under a stochastic network model inspired by Decker and Wattenhofer (2013). We also show via simulations that Barracuda is robust to several real-world factors in the network model.
Graduation Semester
2020-12
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/109389
Copyright and License Information
Copyright 2020 Ranvir Rana

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