arXiv subjects

Michael Wei

Publications and source records attributed to Michael Wei.

4 recordsLinked to original sources

arXiv2024

On Orchestrating Parallel Broadcasts for Distributed Ledgers

This paper introduces and develops the concept of ``ticketing'', through which atomic broadcasts are orchestrated by nodes in a distributed system. The paper studies different ticketing regimes that allow parallelism, yet prevent slow nodes from hampering overall progress. It introduces a hybrid scheme which combines managed and unmanaged ticketing regimes, striking a balance between adaptivity and resilience. The performance evaluation demonstrates how managed and unmanaged ticketing regimes benefit throughput in systems with heterogeneous resources both in static and dynamic scenarios, with the managed ticketing regime performing better among the two as it adapts better. Finally, it demonstrates how using the hybrid ticketing regime performance can enjoy both the adaptivity of the managed regime and the liveness guarantees of the unmanaged regime.

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arXiv2023

BBCA-LEDGER: High Throughput Consensus meets Low Latency

This paper presents BBCA-LEDGER, a Byzantine log replication technology for partially synchronous networks enabling blocks to be broadcast in parallel, such that each broadcast is finalized independently and instantaneously into an individual slot in the log. Every finalized broadcast is eventually committed to the total ordering, so that all network bandwidth has utility in disseminating blocks. Finalizing log slots in parallel achieves both high throughput and low latency. BBCA-LEDGER is composed of two principal protocols that interweave together, a low-latency/high-throughput happy path, and a high-throughput DAG-based fallback path. The happy path employs a novel primitive called BBCA, a consistent broadcast enforcing unique slot numbering. In steady state, BBCA ensures that a transaction can be committed with low latency, in just 3 network steps. Under network partitions or faults, we harness recent advances in BFT and build a fallback mechanism on a direct acyclic graph (DAG) created by BBCA broadcasts. In this manner, BBCA-LEDGER exhibits the throughput benefits of DAG-based BFT in face of gaps.

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arXiv2020

Rainblock: Faster Transaction Processing in Public Blockchains

Public blockchains like Ethereum use Merkle trees to verify transactions received from untrusted servers before applying them to the blockchain. We empirically show that the low throughput of such blockchains is due to the I/O bottleneck associated with using Merkle trees for processing transactions. We present RAINBLOCK, a new architecture for public blockchains that increases throughput without affecting security. RAINBLOCK achieves this by tackling the I/O bottleneck on two fronts: first, decoupling transaction processing from I/O, and removing I/O from the critical path; second, reducing I/O amplification by customizing storage for blockchains. RAINBLOCK uses a novel variant of the Merkle tree, the Distributed Sharded Merkle tree (DSM-TREE) to store system state. We evaluate RAINBLOCK using workloads based on public Ethereum traces (including smart contracts) and show that RAINBLOCK processes 20K transactions per second in a geo-distributed setting with four regions spread across three continents.

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arXiv2019

Storm: a fast transactional dataplane for remote data structures

RDMA is an exciting technology that enables a host to access the memory of a remote host without involving the remote CPU. Prior work shows how to use RDMA to improve the performance of distributed in-memory storage systems. However, RDMA is widely believed to have scalability issues, due to the amount of active protocol state that needs to be cached in the limited NIC cache. These concerns led to several software-based proposals to enhance scalability by trading off performance. In this work, we revisit these trade-offs in light of newer RDMA hardware and propose new guidelines for scaling RDMA. We show that using one-sided remote memory primitives leads to higher performance compared to send/receive and kernel-based systems in rack-scale environments. Based on these insights, we design and implement Storm, a transactional dataplane using one-sided read and write-based RPC primitives. We show that Storm outperforms eRPC, FaRM, and LITE by 3.3x, 3.6x, and 17.1x, respectively, on an Infinband EDR cluster with Mellanox ConnectX-4 NICs.

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