Scaling Blockchains: A Comprehensive Survey
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Simulation or modelingConsensus signal: none
- Genre
- Candidate signal: EmpiricalConsensus signal: none
- Teacher disagreement score
- 0.761
- Threshold uncertainty score
- 0.482
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
- Teacher spread
- 0.230 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Blockchain (e.g., Bitcoin and Ethereum) has drawn much attention and has been widely-deployed in recent years. However, blockchain scalability is emerging as a challenging issue. This paper outlines the existing solutions to blockchain scalability, which can be classified into two categories: first layer and second layer solutions. First layer solutions propose modifications to the blockchain (i.e., changing the blockchain structure, such as block size) while second layer solutions propose mechanisms that are implemented outside of the blockchain. In particular, we focus on sharding as a promising first layer solution to the scalability issue; the basic idea behind sharding is to divide the blockchain network into multiple committees, each processing a separate set of transactions. More specifically, (a) we propose a taxonomy based on committee formation and intra-committee consensus; and (b) we compare the main existing sharding-based blockchain protocols. We also present a performance-based comparative analysis (i.e., throughput and latency), of the advantages, and disadvantages in existing scalability solutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- IEEE Access
- Topic
- Blockchain Technology Applications and Security
- Field
- Computer Science
- Canadian institutions
- Université de Montréal
- Funders
- Université Mohammed VI Polytechnique
- Keywords
- BlockchainScalabilityComputer scienceLayer (electronics)Distributed computingSet (abstract data type)Latency (audio)ScalingBlock (permutation group theory)Computer networkComputer architectureComputer securityTelecommunicationsDatabaseNanotechnology
- Has abstract in OpenAlex
- yes