50,612 research outputs found
A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks
© 2013 IEEE. The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and data-driven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability, and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this paper, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of decentralized consensus in blockchain networks, our in-depth review of the state-of-the-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review of the strategy adopted for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey of the emerging applications of blockchain networks in a broad area of telecommunication. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions
Decentralized Generalized Approximate Message-Passing for Tree-Structured Networks
Decentralized generalized approximate message-passing (GAMP) is proposed for
compressed sensing from distributed generalized linear measurements in a
tree-structured network. Consensus propagation is used to realize average
consensus required in GAMP via local communications between adjacent nodes.
Decentralized GAMP is applicable to all tree-structured networks that do not
necessarily have central nodes connected to all other nodes. State evolution is
used to analyze the asymptotic dynamics of decentralized GAMP for zero-mean
independent and identically distributed Gaussian sensing matrices. The state
evolution recursion for decentralized GAMP is proved to have the same fixed
points as that for centralized GAMP when homogeneous measurements with an
identical dimension in all nodes are considered. Furthermore, existing
long-memory proof strategy is used to prove that the state evolution recursion
for decentralized GAMP with the Bayes-optimal denoisers converges to a fixed
point. These results imply that the state evolution recursion for decentralized
GAMP with the Bayes-optimal denoisers converges to the Bayes-optimal fixed
point for the homogeneous measurements when the fixed point is unique.
Numerical results for decentralized GAMP are presented in the cases of linear
measurements and clipping. As examples of tree-structured networks, a
one-dimensional chain and a tree with no central nodes are considered.Comment: submitted to IEEE Trans. Inf. Theor
On the Minimal Knowledge Required for Solving Stellar Consensus
Byzantine Consensus is fundamental for building consistent and fault-tolerant
distributed systems. In traditional quorum-based consensus protocols, quorums
are defined using globally known assumptions shared among all participants.
Motivated by decentralized applications on open networks, the Stellar
blockchain relaxes these global assumptions by allowing each participant to
define its quorums using local information. A similar model called Consensus
with Unknown Participants (CUP) studies the minimal knowledge required to solve
consensus in ad-hoc networks where each participant knows only a subset of
other participants of the system. We prove that Stellar cannot solve consensus
using the initial knowledge provided to participants in the CUP model, even
though CUP can. We propose an oracle called sink detector that augments this
knowledge, enabling Stellar participants to solve consensus.Comment: Preprint of a paper to appear at the 43rd IEEE International
Conference on Distributed Computing Systems (ICDCS 2023
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