DOCSLIB.ORG

Leaderless Byzantine Fault Tolerance

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Leaderless Byzantine Fault Tolerance Leaderless Byzantine Fault Tolerance Tian Qin Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2020-121 http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-121.html May 29, 2020 Copyright © 2020, by the author(s). All rights reserved. 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. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Acknowledgement I would like to express my appreciation to Jian Liu and Peng Gao for their guidance, advice, and feedbacks during this research work. Leaderless Byzantine Fault Tolerance by Tian Qin Research Project Submitted to the Department of Electrical Engineering and Computer Sciences, University of California at Berkeley, in partial satisfaction of the requirements for the degree of Master of Science, Plan II. Approval for the Report and Comprehensive Examination: Committee: Professor Dawn Song Research Advisor (Date) * * * * * * * Professor Sylvia Ratnasamy Second Reader Leaderless Byzantine Fault Tolerance ABSTRACT transaction commitment is deterministic; it is built upon a gossip In this work, we propose Leaderless Byzantine Fault Tolerance protocol to relay messages and data across the whole network, prac- (LBFT), a novel consensus algorithm that combines Snowball algo- tical Byzantine Fault Tolerance algorithm to commit transactions rithm and Practical Byzantine Fault Tolerance (pBFT) algorithm, in a deterministic manner, and Snowball to realize decentralization two existing consensus algorithms. Achieving consensus in decen- of nodes (i.e. leaderless). tralized systems has been dicult as they lack certain properties In this paper, we identied the requirements of a leaderless con- that many algorithms assume. Our approach looks to take advan- sensus protocol, designed algorithmic architecture, built a gossip tage of the decentralized aspect of Snowball and the deterministic protocol, the Snowball protocol, the pBFT protocol, and the LBFT property of pBFT so that the weaknesses of Snowball’s probabilis- protocol, integrated optimization techniques such as transaction tic property and pBFT’s reliance on "leader" are eliminated. The pipeline to mitigate loss in performance of LBFT compared to pBFT, algorithm we propose is applicable to decentralized systems such and tested, evaluated, and cross-compared each of the four proto- as blockchain systems even though Snowball and pBFT both make cols. stronger assumptions than decentralized systems allow. By simu- Thus, this paper makes the following contributions: lating real-world environments and comparing with pBFT perfor- Design and Analysis of LBFT, which assumes asynchro- • mances, we show that LBFT is feasible in the context of real-world nous network decentralized systems and has sucient performances that are close System implementation and testing of LBFT • to those of pBFT. 2 BACKGROUND Machines in a distributed system have shared states. Consensus is 1 INTRODUCTION unanimous agreement on state values across a network. A consen- A distributed system is simply a group of computers working to- sus algorithm is a procedure that achieves such states in a network. gether. Distributing a system brings many advantages such as hori- In other words, consensus algorithms coordinate network nodes in zontal scalability, fault tolerance, low latency, etc. A core feature of a distributed setting. The ability to achieve consensus is at the core a distributed system is that it should appear as a single computer of every distributed system. during all interactions with users. The scalability, parallelism, and To create formal proofs of consensus algorithms, distributed communications among dierent machines in a distributed sys- systems are generally assumed to be synchronous, partially syn- tem shall be abstracted away. The power of distributed systems chronous, or asynchronous. These three timing models each have comes with a downside: achieving consensus is dicult due to dierent properties regarding latency of message transmissions faults, malicious actors, and many other factors and without agree- among network nodes. In a synchronous model, which has the ment/coordination among individual nodes, a distributed system strongest assumptions, message transmissions delays have a known fails. upper bound, message transmissions follow FIFO (rst in, rst out) Practical Byzantine Fault Tolerance [4] is one consensus algo- rule, and local clocks of all nodes in the network are synchronized; rithm that carries out a three-phase procedure: pre-prepare, prepare, in a partially synchronous model, there exists an upper bound on and commit. pBFT is robust for distributed systems with the weak- transmission delay but it’s unknown; in an asynchronous model, est assumptions: asynchronous networks, a type of networks where nodes’ clocks are not synchronized and message transmissions can consensus is very dicult due to a complete lack of understanding be delayed for an arbitrary amount of time and there’s no order of timing of message transmissions. in message arrival. In The choice of timing model assumption is Snowball [1] is a consensus algorithm that takes majority votes important to correctness and liveness of consensus algorithms as from random subsets of the network to achieve network-wide agree- a distributed system’s timing model determines whether a node ment in a probabilistic way. It is robust in partially synchronous can dierentiate between a peer that has failed and one that is networks. just taking time to respond. Assumption of a more friendly timing Both pBFT and Snowball are robust in presence of Byzantine model makes designing consensus algorithms much easier. faults, which are conditions where there’s incomplete information The asynchronous model has the weakest assumptions and re- on whether a node has failed. However, each has its downsides. sembles real-world systems the most, where nodes fail and messages During each round of consensus execution, pBFT relies heavily on a get dropped all the time. Consequently, reaching consensus in a node being the "leader" and such a centralized concept renders the real-world distributed system is dicult in the presence of pro- algorithm vulnerable to numerous attacks. Unlike pBFT, Snowball cess failures and communication failures. These challenges are laid is decentralized, but its consensus is probabilistic and is not robust out in many theoretical scenarios such as The Byzantine Generals’ in asynchronous networks. Problem, which describes a situation where consensus is very di- We propose a new consensus algorithm that doesn’t rely on cult with presence of corrupt parties and false information. Many any notion of leaders and works in asynchronous environments distributed consensus algorithms have a notion of leaders, which - Leaderless Byzantine Fault Tolerance (LBFT). It is applicable to is a subset of all network nodes that make core decisions on how decentralized systems, in particular blockchains; it is leaderless and the system should move forward. One example practical Byzantine deterministic: there is no dierentiation among network nodes and Fault Tolerance (Castro and Liskov, 1999). It proposes a pre-prepare, 2 prepare, commit process Not to mention that such a notion of leader On the other hand, blockchain systems have shown potential renders the system more vulnerable, these consensus algorithms in revolutionizing many elds such as nance, supply chain, and are not applicable to decentralized systems such as blockchains, internet of things. However, current widely deployed consensus which are more robust than traditional distributed systems and thus algorithms have dierent drawbacks: ineciency, unfairness, etc. can uphold fewer assumptions that many consensus algorithms As consensus algorithms have been a bottleneck for adoption of rely on. blockchain systems, an ecient and secure consensus algorithm for Practical Byzantine Fault Tolerance [4] is a consensus algorithm blockchain systems has been a widely pursued area of research and that was introduced in the late 90s and its consensus procedure is our proposed algorithm also looks to contribute to it. By combining carried out in three phases: pre-prepare, prepare, and commit. Nodes pBFT and Snowball, we aim to arrive at an algorithm that’s robust move through a succession of congurations called views and in in decentralized systems. each view, one node is assigned as the primary. The pre-prepare and prepare phases guarantee that non-faulty nodes agree on a total 3 OVERVIEW order of requests within a view and the commit phase guarantees a total order of requests across views. In pre-prepare phase, the The protocol consists of two layers of implementation: primary assigns a sequence number to the request and multicasts a peer-to-peer (p2p) base layer the request, digest of the request, the sequence number, and the • a consensus layer on top of the p2p layer that implements view number to all other nodes, who then transition to prepare • a deterministic and leaderless consensus algorithm built phase if message and signature are correct and sequence number upon Snowball and practical Byzantine Fault Tolerance and view number are valid. In prepare phase, each node multicasts to every other
Load more

Recommended publications
  • Chapter 1 from Byzantine Consensus to Blockchain Consensus
    Chapter 1 From Byzantine Consensus to Blockchain Consensus CONTENTS 1.1 Introduction ....................................................... 3 1.2 Byzantine Consensus .............................................. 6 1.2.1 On System Models ........................................ 6 1.2.2 Byzantine Consensus Definitions .......................... 7 1.2.3 FLP Impossibility ......................................... 9 1.2.4 Byzantine Consensus Patterns ............................. 12 1.2.5 Hybrid Models to Reduce Processes ....................... 13 1.2.6 Randomization ............................................ 15 1.3 Blockchains with Nakamoto Consensus ............................. 19 1.3.1 Bitcoin’s Blockchain and Consensus ....................... 19 1.3.2 Blockchain Applications ................................... 24 1.3.3 Nakamoto Consensus Variants ............................. 27 1.4 Blockchains with Byzantine Consensus ............................. 30 1.4.1 Permissioned Blockchains with Byzantine Consensus ....... 30 1.4.2 Permissionless Blockchains with Hybrid Consensus ........ 32 1.5 Conclusion ........................................................ 34 3 4 ⌅ Saunders Template 1.1 Introduction Blockchain is an exciting new technology that is making headlines worldwide. The reasons behind the success of a technology are often unclear, but in the case of block- chain it is safe to say that an important factor is that is has two killer apps, not a single one. The first killer app are cryptocurrencies, as the original blockchain is the core of Bitcoin [128], the first cryptocurrency and the one that is fostering the adoption of cryptocurrencies. The second killer app are smart contracts, first introduced in the Ethereum system [40], with their promise of computerizing legal contracts and of supporting a countless number of applications [161, 153, 90]. Moreover, the sky seems to be the limit for the applications people are imagining for blockchain. A blockchain is essentially a secure, unmodifiable, append-only, log of transac- tions.
    [Show full text]
  • A Survey of Distributed Consensus Protocols for Blockchain Networks
    1 A Survey of Distributed Consensus Protocols for Blockchain Networks Yang Xiao∗, Ning Zhang†, Wenjing Lou∗, Y. Thomas Hou∗ ∗Virginia Polytechnic Institute and State University, VA, USA †Washington University in St. Louis, MO, USA Abstract—Since the inception of Bitcoin, cryptocurrencies participants. On the other hand, blockchain is also known for and the underlying blockchain technology have attracted an providing trustworthy immutable record keeping service. The increasing interest from both academia and industry. Among block data structure adopted in a blockchain embeds the hash various core components, consensus protocol is the defining technology behind the security and performance of blockchain. of the previous block in the next block generated. The use of From incremental modifications of Nakamoto consensus protocol hash chain ensures that data written on the blockchain can not to innovative alternative consensus mechanisms, many consensus be modified. In addition, a public blockchain system supports protocols have been proposed to improve the performance of third-party auditing and some blockchain systems support a the blockchain network itself or to accommodate other specific high level of anonymity, that is, a user can transact online application needs. In this survey, we present a comprehensive review and anal- using a pseudonym without revealing his/her true identity. ysis on the state-of-the-art blockchain consensus protocols. To The security properties promised by blockchain is unprece- facilitate the discussion of our analysis, we first introduce the dented and truly inspiring. Pioneering blockchain systems such key definitions and relevant results in the classic theory of fault as Bitcoin have greatly impacted the digital payment world.
    [Show full text]
  • A MILP Model for a Byzantine Fault Tolerant Blockchain Consensus
    future internet Article A MILP Model for a Byzantine Fault Tolerant Blockchain Consensus Vitor Nazário Coelho 1,* , Rodolfo Pereira Araújo 2, Haroldo Gambini Santos 3, Wang Yong Qiang 4 and Igor Machado Coelho 5,* 1 OptBlocks, Avenida Jo ao Pinheiro, 274 Sala 201-Lourdes, Belo Horizonte-MG 30130-186, Brazil 2 Graduate Program in Computational Sciences (PPG-CComp), Universidade do Estado do Rio de Janeiro, Rua S ao Francisco Xavier, 524-Maracan a, Rio de Janeiro-RJ 20550-013, Brazil; [email protected] 3 Department of Computer Science, Universidade Federal de Ouro Preto, Campus Morro do Cruzeiro, Ouro Preto-MG 35400-000, Brazil; [email protected] 4 Research & Development Department, Neo Global Development, 80, Zhengxue Rd, Shanghai 200082, China; [email protected] 5 Institute of Computing, Universidade Federal Fluminense, Av. Gal. Milton Tavares de Souza, São Domingos, Niterói-RJ 24210-310, Brazil * Correspondence: [email protected] (V.N.C.); [email protected] (I.M.C.) Received: 30 September 2020; Accepted: 26 October 2020; Published: 29 October 2020 Abstract: Mixed-integer mathematical programming has been widely used to model and solve challenging optimization problems. One interesting feature of this technique is the ability to prove the optimality of the achieved solution, for many practical scenarios where a linear programming model can be devised. This paper explores its use to model very strong Byzantine adversaries, in the context of distributed consensus systems. In particular, we apply the proposed technique to find challenging adversarial conditions on a state-of-the-art blockchain consensus: the Neo dBFT. Neo Blockchain has been using the dBFT algorithm since its foundation, but, due to the complexity of the algorithm, it is challenging to devise definitive algebraic proofs that guarantee safety/liveness of the system (and adjust for every change proposed by the community).
    [Show full text]
  • Byzantine Consensus in Asynchronous Message-Passing Systems: a Survey
    Int. J. Critical Computer-Based Systems, Vol. x, No. x, xxxx 1 Byzantine Consensus in Asynchronous Message-Passing Systems: a Survey Miguel Correia*, Giuliana Santos Veronese, Nuno Ferreira Neves and Paulo Verissimo Faculdade de Ciˆenciasda Universidade de Lisboa Campo Grande, 1749-016 Lisboa, Portugal E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract Consensus is a classical distributed systems problem with both theo- retical and practical interest. Asynchronous Byzantine consensus is cur- rently at the core of some solutions for the implementation of highly- resilient computing services. This paper surveys Byzantine consensus in message-passing distributed systems, by presenting the main theo- retical results in the area, the main classes of algorithms and by dis- cussing important issues like the performance and resilience of these algorithms. Keywords: distributed algorithms; distributed systems; consensus; Byzantine faults; arbitrary faults; asynchronous model; message pass- ing; Byzantine consensus Reference to this paper should be made as follows: Correia, M., Veronese, G. S., Neves, N. F. and Verissimo, P. (xxxx) ‘Byzantine Con- sensus in Asynchronous Message-Passing Systems: a Survey’, Int. J. Critical Computer-Based Systems, Vol. x, No. x, pp.xxx–xxx. Biographical notes: Miguel Correia is an assistant professor in the Department of Informatics at the Faculty of Sciences at the University of Lisboa, and an adjunct faculty member of the Carnegie Mellon In- formation Networking Institute. More information about his research can be found at http://www.di.fc.ul.pt/∼mpc.
    [Show full text]
  • Virginia Gold 212-626-0505 [email protected]
    Contact: Virginia Gold 212-626-0505 [email protected] ACM TURING AWARD GOES TO PIONEER WHO ADVANCED RELIABILITY AND CONSISTENCY OF COMPUTING SYSTEMS Microsoft’s Lamport Contributed to Theory and Practice of Building Distributed Computing Systems that Work as Intended NEW YORK, March 18, 2014 – ACM (Association for Computing Machinery) www.acm.org today named Leslie Lamport, a Principal Researcher at Microsoft Research, as the recipient of the 2013 ACM A.M. Turing Award for imposing clear, well-defined coherence on the seemingly chaotic behavior of distributed computing systems, in which several autonomous computers communicate with each other by passing messages. He devised important algorithms and developed formal modeling and verification protocols that improve the quality of real distributed systems. These contributions have resulted in improved correctness, performance, and reliability of computer systems. The ACM Turing Award, widely considered the “Nobel Prize in Computing,” carries a $250,000 prize, with financial support provided by Intel Corporation and Google Inc. ACM President Vint Cerf noted that “as an applied mathematician, Leslie Lamport had an extraordinary sense of how to apply mathematical tools to important practical problems. By finding useful ways to write specifications and prove correctness of realistic algorithms, assuring strong foundation for complex computing operations, he helped to move verification from an academic discipline to practical tool.” Lamport’s practical and widely used algorithms and tools have applications in security, cloud computing, embedded systems and database systems as well as mission-critical computer systems that rely on secure information sharing and interoperability to prevent failure. His notions of safety, where nothing bad happens, and liveness, where something good happens, contribute to the reliability and robustness of software and hardware engineering design.
    [Show full text]
  • Byzantine Fault Tolerance
    Byzantine Fault Tolerance CS 475, Spring 2019 Concurrent & Distributed Systems Review: Why P2P? • Spreads network/cache costs across users instead of provider • No server might mean: • Easier to deploy • Less chance of overload • Single failure won’t take down the system • Harder to attack J. Bell GMU CS 475 Spring 2019 !2 Review: Napster • The good: • Simple • Finding a file is really fast, regardless of how many clients there are - master has it all • The bad: • Server becomes a single point of failure • Server does a lot of processing • Server having all of metadata implies significant legal liabilities J. Bell GMU CS 475 Spring 2019 !3 Review: Gnutella • Gnutella’s search approach is called "flooding" • Cool: • Fully decentralized • Cost of search is distributed - no single node has to search through all of the data • Bad: • Search requires contacting many nodes! • Who can know when your search is done? • What if nodes leave while you are searching? J. Bell GMU CS 475 Spring 2019 !4 Review: BitTorrent • Goal: • Get large files out to as many users as possible, quickly • Usages: • Static bulk content (Big software updates, videos, etc) • User model is cooperative • While downloading a large file, also sharing the parts that you have • After you get the file, keep sharing for a while too • Approach relies on a “tracker” per file J. Bell GMU CS 475 Spring 2019 !5 Is our system well behaved? Byzantine Start talking about for P2P systems Partitions What we’ve done so far Crash-fail J. Bell GMU CS 475 Spring 2019 !6 Byzantine Failures in P2P May I have this totally legal, not copyrighted video please? Sure, here it is! J.
    [Show full text]
  • Distributed Computing Column 36 Distributed Computing: 2009 Edition
    Distributed Computing Column 36 Distributed Computing: 2009 Edition Idit Keidar Dept. of Electrical Engineering, Technion Haifa, 32000, Israel [email protected] It’s now the season for colorful reviews of 2009. While you can read elsewhere about the year in sports, top-40 pop hit charts, people of the year, and so on, I throw my share into the mix with a (biased) review of this year’s major distributed computing events. Awards First, let’s look at awards. This year we learned that two women were recognized with ACM and IEEE prestigious awards for their achievements in, (among other things), distributed computing. Barbara Liskov won the 2008 ACM Turing Award for a range of contributions to practical and theoretical foundations of programming language and system design, some of which are in distributed computing. The award citation mentions her impact on distributed programming, decentralized information flow, replicated storage, and modular upgrading of distributed systems. I include below a short reflection, by Rodrigo Rodrigues, on Barbara Liskov’s Turing Award and legacy. Looking ahead to 2010, it was recently announced that Nancy Lynch is the recipient of the prestigious 2010 IEEE Emanuel R. Piore Award1 for her contributions to foundations of distributed and concurrent computing. The award is given for outstanding contributions in the field of information processing in relation to computer science. Leslie Lamport has won the same award in 2004 for his seminal contributions to the theory and practice of concurrent programming and fault-tolerant computing. The 2009 Edsger W. Dijkstra Prize in Distributed Computing was awarded to Joseph Halpern and Yoram Moses for “Knowledge and Common Knowledge in a Distributed Environment”.
    [Show full text]
  • Modelling and Testing Composite Byzantine-Fault Tolerant Consensus Protocols
    Modelling and Testing Composite Byzantine-Fault Tolerant Consensus Protocols Daniel Lok Capstone Final Report for BSc (Honours) in Mathematical, Computational, and Statistical Sciences Supervised by: Dr. Ilya Sergey AY 2018/2019 i Acknowledgements This capstone would not have been possible without the support of numer- ous friends and faculty. We thank Dr. Ilya Sergey for his invaluable advice on every aspect of this project, as well as his eagerness in teaching and recommending additional sources of information. We would also like to thank Dr. Olivier Danvy for his course Functional Programming and Proving, which provided a rich foundation on which much of this capstone was built. Additionally, we would like to thank the residents and ex-residents of Elm College’s 17th floor for emotional support, and in particular, Yong Kai Yi and Cephas Tan for their helpful comments and advice on the direction, structure, and wording of this manuscript. ii YALE-NUS COLLEGE Abstract B.Sc (Hons) Modelling and Testing Composite Byzantine-Fault Tolerant Consensus Protocols by Daniel LOK Implementing distributed systems is a notoriously difficult task. Program- mers that attempt to build executable versions of published consensus pro- tocols often run into numerous bugs along the way, in part due to the often informal nature of the publications. This project provides a framework to conveniently implement and test models of distributed consensus protocols, with the intention of assisting programmers in formulating “correct” system sematics prior to actual im- plementation. This paper describes the internal workings of the framework, its API, and how to use it to model complex phenomena such as Byzantine faults, modular protocol composition, and asynchrony.
    [Show full text]
  • Enabling Secure and Resource-Efficient Blockchain Networks with VOLT
    Enabling secure and resource-efficient blockchain networks with VOLT Srinath Setty Soumya Basu? Lidong Zhou Michael L. Roberts Ramarathnam Venkatesan Microsoft Research ?Cornell University Abstract per second) at relatively low latency (e.g., a few seconds). This paper describes VOLT, a permissioned blockchain While Byzantine fault-tolerant (BFT) protocols [22, network for a group of autonomous organizations to au- 31, 36, 55] seem to solve the core consensus problem, tomate cross-organizational business processes. Specif- subtle, but fundamental, aspects render these protocols ically, VOLT ensures that a correct member—without insufficient for permissioned blockchain networks, even trusting anyone else—shares a consistent history of trans- though the underlying substrate in BFT remains relevant. actions with other members in the system. VOLT achieves These BFT protocols were primarily designed to replicate this strong security property using the concept of a self- services in a datacenter environment—to guard against verifying ledger: an append-only ledger of transactions crash failures and Byzantine behavior by a subset of the that can be checked locally by a verifier process at each replicas. In the context of permissioned blockchain net- node; the ledger also embeds succinct cryptographic mes- works, the protocol has to be carried out across trusted sages encoding views of members to enable each veri- domains with each member representing a participating fier to locally determine globally-committed transactions. organization (such as a bank), rather than a replica of a To orchestrate this concept, VOLT employs a logically replicated service typically in the same trusted domain. centralized—but untrusted—service provider. We instan- Consequently, the desirable guarantees must be defined tiate the service provider using a highly-available cloud from the perspective of each member, rather than for a service built atop a fault-tolerant cloud storage service.
    [Show full text]
  • Byzantizing Paxos by Refinement
    Byzantizing Paxos by Refinement Leslie Lamport 5 December 2010 Abstract We derive a 3f +1 process Byzantine Paxos consensus algorithm by Byzantizing a variant of the ordinary Paxos algorithm|that is, by having 2f + 1 nonfaulty processes emulate the ordinary Paxos algo- rithm despite the presence of f malicious processes. We have writ- ten a formal, machine-checked proof that the Byzantized algorithm implements the ordinary Paxos consensus algorithm under a suitable refinement mapping. Contents 1 Introduction 1 2 Consensus and Classic Paxos 2 2.1 Consensus . .2 2.2 Paxos Consensus . .2 3 Byzantizing An Algorithm 4 4 Algorithm PCon 7 5 Algorithm BPCon 8 6 Liveness and Learning About Sent Messages 10 6.1 Sending Proofs . 11 6.2 Relaying 1b Messages . 12 7 The Castro-Liskov Algorithm 13 8 The Formal Specifications and Proof 14 9 Conclusion 16 References 16 You can verb anything. Ron Ziegler (quoted by Brian Reid) 1 Introduction The Paxos algorithm [6] has become a standard tool for implementing fault- tolerant distributed systems. It uses 2f + 1 processes to tolerate the benign failure of any f of them. More recently, Castro and Liskov developed a 3f + 1 process algorithm [2] that tolerates f Byzantine (maliciously faulty) processes. Intuitively, their algorithm seems to be a Byzantine version of Paxos. Other algorithms that also seem to be Byzantine versions of Paxos have subsequently appeared [4, 11, 14]. The only previous attempt we know of to explain the relation between a Byzantine Paxos algorithm and ordinary Paxos was by Lampson [13]. He derived both from an abstract, non-distributed algorithm.
    [Show full text]
  • Gosig: Scalable Byzantine Consensus on Adversarial Wide Area Network for Blockchains
    Gosig: Scalable Byzantine Consensus on Adversarial Wide Area Network for Blockchains Peilun Li Guosai Wang Xiaoqi Chen Tsinghua University Tsinghua University Princeton University Wei Xu Tsinghua University Abstract longer have to worry about Sybil attacks [21], there are Existing Byzantine fault tolerance (BFT) protocols still some other significant challenges. face significant challenges in the consortium blockchain The blockchain is replicated to each participant, and scenario. On the one hand, we can make little assump- the key problem is how to reach consensus on these repli- tions about the reliability and security of the underlying cas. Comparing to traditional distributed transaction sys- Internet. On the other hand, the applications on consor- tems, the three biggest challenges of a blockchain are: tium blockchains demand a system as scalable as the Bit- 1) Players are from different organizations without coin but providing much higher performance, as well as mutual trust. Failures, even Byzantine failures, are com- provable safety. We present a new BFT protocol, Gosig, mon. Thus, we cannot rely on a small quorum (e.g., that combines crypto-based secret leader selection and Chubby [9] or ZooKeeper [27]) for consensus. Instead, multi-round voting in the protocol layer with implemen- we need Byzantine consensus and allow all players to tation layer optimizations such as gossip-based message participate, i.e., supporting a consensus group with thou- propagation. In particular, Gosig guarantees safety even sands of servers. in a network fully controlled by adversaries, while pro- 2) The system runs on an open Internet. The network viding provable liveness with easy-to-achieve network can drop/delay communication arbitrarily.
    [Show full text]
  • Asynchronous Byzantine Fault Tolerant
    A definition The Byzantine Generals Problem Leslie Lamport, Robert Shostak, and Marshall Pease • Byzantine (www.m-w.com): ACM TOPLAS 1982 1: of, relating to, or characteristic of the ancient city of Byzantium … Practical Byzantine Fault Tolerance 4b: intricately involved : labyrinthine <rules of Byzantine Miguel Castro and Barbara Liskov complexity> OSDI 1999 • Lamport’s reason: “I have long felt that, because it was posed as a cute problem about philosophers seated around a table, Dijkstra's dining philosopher's problem received much more attention than it deserves.” (http://research.microsoft.com/users/lamport/pubs/pubs.html#byz) Byzantine Generals Problem Synchronous, Byzantine world • Concerned with (binary) atomic broadcast – All correct nodes receive same value Synchronous Asynchronous – If broadcaster correct, correct nodes receive broadcasted value • Can use broadcast to build consensus protocols (aka, agreement) – Consensus: think Byzantine fault-tolerant (BFT) Paxos Fail-stop Byzantine Practical Byzantine Fault Tolerance: Cool note Asynchronous, Byzantine Example Byzantine fault-tolerant system: ! Seawolf submarine’s control system Synchronous Asynchronous Sims, J. T. 1997. Redundancy Management Software Services for Seawolf Ship Control System. In Proceedings of the 27th international Symposium on Fault-Tolerant Computing (FTCS '97) (June 25 - 27, 1997). FTCS. IEEE Computer Society, Washington, DC, 390. But it remains to be seen if commodity distributed systems are willing to pay to Fail-stop have so many replicas in a system Byzantine Distributed systems Practical Byzantine Fault Tolerance • Async BFT consensus: Need 3f+1 nodes – Sketch of proof: Divide 3f nodes into three groups of f, left, •Why async BFT? BFT: middle, right, where middle f are faulty.
    [Show full text]