Table of Contents |
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Reference_description_with_linked_URLs________________________________________ | Notes______________________________________________________________ |
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Fast-Fabric POC whitepaper | |
Fast-Fabric slide deck | |
https://github.com/IBM/hlf-internals https://github.com/IBM/hlf-internals/blob/master/docs/index.md | Fabric v1.4x architecture internals Christian Vecchiola |
https://www.meetup.com/es-ES/Hyperledger-Madrid/events/270078655/ | Fabric performance best practices meetup notes |
https://image.samsungsds.com/us/en/insights/res/__icsFiles/afieldfile/2019/02/ 16/2019.02.15_Blockchain_AcceleratingThroughputinPermissionedBlockchain Networks.pdf?elqTrackId=8f12b155e7b849998e39adbe583b9a66&elqaid=507&elqat=2 | Samsung Accelerator add in for Fabric that may speed transaction throughput up to 10x ( expect 2x ) |
Performance Use Cases | |
dltledgers automates Air Asia commodity freight transport on Fabric – tested at 2,000 TPS | |
Empirical Performance Analysis of Hyperledger LTS for Small and Medium Enterprises ilnk Enterprisesfabric-performance-v1.2-mdpi.com-Empirical Performance Analysis of Hyperledger LTS for Small and Medium Enterprises.pdf pdf | Fabric LTS 1.2 performance for medium size companies *** |
https://pdfs.semanticscholar.org/9e51/e5721d0287d5b6e1a2296b7830857f884d7b.pdf | 2018 benchmarking of Fabric on LTS v1.2 Kafka |
Performance strategies | |
https://www.consortia.io/blog/scale-your-blockchain-dlt-based-supply-chain/ | |
Performance articles, resources | |
https://learn.bybit.com/blockchain/fastest-cryptocurrencies-high-tps/ | 2023 comparison on DLT TPS, finalization estimates Polygon (MATIC) is a blockchain that seeks to scale the Ethereum network by supporting multiple scaling solutions, including Layer 2 and sidechain solutions. It boasts a high throughput of 7,000 TPS and a finality time of 2–3 seconds Fabric v2x
Fabric v3x
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https://diablobench.github.io/ | Project Diablo compares blockchain performance Diablo is a benchmark suite to evaluate blockchain systems on the same ground. |
Key Concepts
Blockchain Performance Concepts
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- buffer bc writes async
- minimize write size
- transaction aggregation
block multiple transactions and hashes into single transactions using external index to find the block.transaction id to get the hash for proof- create external index to individual transactions as async process ( not good for real-time confirmations )
- leverage off-chain and world state databases for transaction updates and reads vs blockchain reads
- push transaction data to encrypted, compressed blobs with NUK key sets, hash the blob & key sets, write hash and (optional) key sets to a block
- use ZK rollups on off-chain transactions for data privacy, minimize data on-chain with rollup hashes, NUKs in hashed blocks with indexes of transaction keys to blocks for fast reads
- consider transaction, block proof design that rolls up to the next level ( proof of proofs )
- anonymous state pinning article is another approach with advantages on information hiding
- sharding for parallel processing
- horizontal scale
- minimize validator needs for transaction consensus
- use ISSMR models to transmit on blockchain network vs simple leader to all propagation
- vertical scale with more powerful nodes
- minimize nodes needed
- use logical members layer vs physical nodes to add orgs, accounts
- id the right block validation model to fit the use case driving the minimum node network design
- upsize cluster
- create logical acid transaction with confirmation prior to write completion - optimistic write w auto retry if failed - separates commit vs finalization
- use off-chain data to answer most queries
- use centralized network where the use case fits
- use logical shards for the blockchain where it fits
- use caching where it helps
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