[PDF] BlockEmulator: An Emulator Enabling to Test Blockchain Sharding Protocols | Semantic Scholar (2024)

Hammer is introduced, a general blockchain evaluation framework that consists of two key components: workload prediction and asynchronous task processing, providing a more realistic evaluation of blockchain performance.

The experimental results show that the proposed Fine-tuned Lock protocol outperforms the SOTA Lock in terms of transaction makespan, and enables real-time processing of the affected transactions during account migration.

The proposed Broker2Earn protocol is a decentralized finance protocol that works as an incentive mechanism for blockchain users who choose to become brokers and can benefit the sharded blockchain since it can efficiently spend each staked liquidity provided by brokers on diminishing CTXs.

SPRING is presented, the first deep-reinforcement-learning(DRL)-based sharding framework for state placement that considers the cross-shard transaction ratio and workload balancing and employs DRL to learn the effective state placement policy.

A fine-grained account-allocation strategy that solves the tradeoff between such two metrics as a network-partition problem and demonstrates that the proposed protocol outperforms other baselines in terms of throughput, latency, cross-shard TX ratio, and the queue size of transaction pool.

BrokerChain is a cross-shard blockchain protocol devised for the account/balance-based state sharding that exploits fine-grained state partition and account segmentation and outperforms other solutions in terms of system throughput, transaction confirmation latency, the queue size of transaction pool, and workload balance.

The Asynchronous Consensus Zones are introduced, which scales blockchain system linearly without compromising decentralization or security, and eventual atomicity is proposed to ensure transaction atomicity across zones, which achieves the efficient completion of transactions without the overhead of a two-phase commit protocol.

LB-Chain is a novel sharding system, called LB-Chain, which dynamically balances the transaction load on different shards by periodically migrating active accounts from heavily-loaded shards to less-loaded ones, leading to improved fairness in the system.

CoChain is proposed: a blockchain sharding system that can securely configure small shards for enhanced concurrency that allows some shards to be corrupted and achieves 35x throughput gain with 6,000+ nodes.

GriDB is presented, the first scalable blockchain database, by designing a novel off-chain cross-shard mechanism for efficient cross- shard database services and introduces several new authenticated data structures (ADS) to extend the threat model and reduce the complexity of traditional accumulator-based ADS.

A deterministic and fast allocation scheme TxAllo is proposed to dynamically infer the allocation of accounts and their associated transactions and it directly optimizes the system throughput, considering both the number of cross-shard transactions and the workload balance among shards.

This paper proposes $\mathcal{S}$-Store, a scalable data storage technique towards permissioned blockchain sharding based on Aggregate Merkle B+ tree (AMB-tree), which outperforms existing techniques by one order of magnitude in terms of transaction execution, data transmission, and committee addition.

This paper proposes two new strategies: power adjusting and bribery racing, and introduces two novel mining attacks, Power Adjusting Withholding (PAW) and Bribery Selfish Mining (BSM), which can increase the reward of attackers.

This paper introduces a new attack model that combines a double-spend attack with a Sybil attack in the Bitcoin network and develops the probability of success of this new attack in mathematics forms and analyze this attack model from the perspective of economics.

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