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Proceedings ArticleDOI

A Secure Sharding Protocol For Open Blockchains

TLDR
ELASTICO is the first candidate for a secure sharding protocol with presence of byzantine adversaries, and scalability experiments on Amazon EC2 with up to $1, 600$ nodes confirm ELASTICO's theoretical scaling properties.
Abstract
Cryptocurrencies, such as Bitcoin and 250 similar alt-coins, embody at their core a blockchain protocol --- a mechanism for a distributed network of computational nodes to periodically agree on a set of new transactions. Designing a secure blockchain protocol relies on an open challenge in security, that of designing a highly-scalable agreement protocol open to manipulation by byzantine or arbitrarily malicious nodes. Bitcoin's blockchain agreement protocol exhibits security, but does not scale: it processes 3--7 transactions per second at present, irrespective of the available computation capacity at hand. In this paper, we propose a new distributed agreement protocol for permission-less blockchains called ELASTICO. ELASTICO scales transaction rates almost linearly with available computation for mining: the more the computation power in the network, the higher the number of transaction blocks selected per unit time. ELASTICO is efficient in its network messages and tolerates byzantine adversaries of up to one-fourth of the total computational power. Technically, ELASTICO uniformly partitions or parallelizes the mining network (securely) into smaller committees, each of which processes a disjoint set of transactions (or "shards"). While sharding is common in non-byzantine settings, ELASTICO is the first candidate for a secure sharding protocol with presence of byzantine adversaries. Our scalability experiments on Amazon EC2 with up to $1, 600$ nodes confirm ELASTICO's theoretical scaling properties.

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Citations
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Book ChapterDOI

Revisiting Practical Byzantine Fault Tolerance Through Blockchain Technologies

TL;DR: It is highlighted that Byzantine fault tolerance should be considered a practical and fundamental building block for modern long-running and safety critical systems and that the principles, mechanisms, and blockchain technologies themselves could help improve the security and quality of such systems.
Journal ArticleDOI

Performance Analysis of Distributed Processing System using Shard Selection Techniques on Elasticsearch

TL;DR: The main goal is to develop a mechanism to handle large scale data processing and searching operations using efficient sharding technique to enhance the performance of distributed processing systems by applying effective shard partitioning and efficient shard selection techniques.
Proceedings ArticleDOI

Trends in Development of Databases and Blockchain

TL;DR: This work explains how the CAP (Consistency, Availability, Partition tolerance) theorem known for databases influenced the DCS (Decentralization, Consistsency, Scalability) theorem for the blockchain systems and postulates a ”DCS-satisfiability conjecture.
Journal ArticleDOI

TD-Root: A trustworthy decentralized DNS root management architecture based on permissioned blockchain

TL;DR: A novel consensus algorithm, in which credence value and penalty mechanism are introduced to ensure the strong consistency, scalability, and security of TD-Root is designed, which is a tamper-proofing architecture and can tolerate one-third of malicious root servers behaving arbitrarily.
Book ChapterDOI

Payment Network Design with Fees

TL;DR: In this article, the problem of network design with fees for payment channels from the perspective of a payment service provider (PSP) is studied, and the optimal graph structure and fee assignment to maximize the PSP's profit is examined.
References
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Book ChapterDOI

The Byzantine generals problem

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The Sybil Attack

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Distributed algorithms

Nancy Lynch
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Proceedings ArticleDOI

Practical Byzantine fault tolerance

TL;DR: A new replication algorithm that is able to tolerate Byzantine faults that works in asynchronous environments like the Internet and incorporates several important optimizations that improve the response time of previous algorithms by more than an order of magnitude.
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