Scalability trilemma is a classical research topic in the area of blockchains. To defeat such trilemma, many previous solutions have been proposed. However, none of those previous solutions can break such scalability trilemma. In this paper, we present a new Layer2 blockchain called W3Chain, which is promising to deliver high transactions per second (TPS) while defeating the scalability trilemma of a public blockchain. To enable the claimed performance, we particularly design our W3Chain by decoupling the correctness of the blockchain into two parts and adopting several crucial technical issues such as the reconfiguration of committees, the design of query APIs, and the handling of cross-shard transactions. We also propose a Time-Beacon Chain (TBChain) to record pivotal data of W3Chain. To show the correctness and safety features, we rigorously analyze multiple properties of W3Chain, including decentralization, scalability, and security under typical attacks. Finally, we conduct extensive simulations using Ethereum's historical transactions to examine the proposed W3Chain. The evaluation results show that our W3Chain can achieve a TPS as high as 10K+, and much lower transaction confirmation latency compared with Ethereum.

In a sharded blockchain, transactions are processed by a number of parallel committees. Thus, the transaction throughput can be largely boosted. A problem is that some groups of blockchain nodes consume large latency to form committees at the beginning of each epoch. Moreover, the heterogeneous processing capabilities of different committees also result in imbalanced consensus latency. Such imbalanced two-phase latency brings a large cumulative age to the transactions pending in transaction pool. Consequently, the blockchain throughput can be significantly degraded. We believe that a good committee-scheduling strategy can reduce the cumulative age of transactions, and thus benefit the throughput. However, we have not yet found a committee-scheduling mechanism that works for accelerating block formation in the context of blockchain sharding. To this end, this paper studies a fine-balanced tradeoff between the transactions’ throughput and their cumulative age in a large-scale sharded blockchain. We formulate this tradeoff as a utility-maximization problem, which is proved NP-hard. To solve this problem, we propose an online distributed Stochastic-Exploration (SE) algorithm, which guarantees a near-optimal system utility. We then rigorously analyze three theoretical properties of the proposed algorithm, including the theoretical convergence time, the probability of committees’ failure due to Sybil attacks, as well as the performance perturbation brought by committees’ offline events. Finally, we evaluate the proposed algorithm using the dataset of real-world blockchain transactions. The simulation results demonstrate that the proposed SE algorithm outperforms other baselines in terms of system utility, the valuable degree of yielded solutions, latency, and throughput performance.