Sharding is one of the most promising technologies for significantly increasing blockchain transaction throughput. However, as the number of shards increases, the ratio of cross-shard transactions in existing blockchain sharding protocols gradually approaches 100%. Since cross-shard transactions consume many times more resources than intra-shard transactions, the processing overhead of cross-shard transactions already accounts for the majority of the total overhead of the sharding system. There is a very large gap between the transaction throughput of the sharding system and its theoretical upper limit. In this article, we propose Estuary, a novel low cross-shard blockchain sharding protocol. Taking the state model as an entry point, Estuary designs a multi-level state model and state splitting and aggregation mechanism. It decouples the identity and quantity of state units, enabling transactions between users to be completed within one shard. Only when the state quantity for all shards of a user is insufficient a small number of cross-shard transactions are required. On this basis, we propose a community overlap propagation algorithm for sharding. It defines the users’ belonging coefficients of each shard and optimizes the state distribution so that the state distribution can better match the transaction characteristics between users. Finally, we develop an analysis framework for the sharding protocol and experiment with real Bitcoin transactions. The evaluation results show that compared to the state-of-the-art sharding protocol, Estuary reduces the ratio of cross-shard transactions by 88.54% and achieves more than 1.85 times the throughput improvement (92.98% of the theoretical upper limit).

Enterprise-grade permissioned blockchain systems provide a promising infrastructure for data sharing and cooperation between different companies. However, performance bottlenecks seriously hinder the adoption of these systems in many industrial applications that process complex business logic and huge transaction volumes. Our research identifies two key factors that limit the system performance: 1) At the block level, the serial dependency of inter-block processing severely limits the system throughput. A new block must wait for the completion of all previous blocks. 2) At the transaction level, the lack of efficient intra-block transactions concurrency makes it difficult to achieve high performance, especially when dealing with multiple CPU-heavy contracts which are commonly used in industrial scenarios. In this paper, we present FISCO-BCOS, an enterprise-grade permissioned blockchain system with high performance. To overcome serial limitations and fully utilize machine resources, FISCO-BCOS introduces Block Level Pipelining (BLP) workflow to process blocks in a pipeline manner. In addition, a scheduling algorithm Deterministic Multi-Contract (DMC) is designed to efficiently execute transactions in parallel. Under BLP and DMC, FISCO-BCOS achieves inter-block and intra-block paralleling to meet high-performance requirements in industrial application scenarios. We conducted experiments on two popular test workloads and compared FISCO-BCOS with state-of-the-art platforms in academia and industry such as BIDL and Hyperledger Fabric (HLF). The result shows that FISCO-BCOS achieves 7.4 times and 28.4 times the throughput of BIDL and HLF, respectively, with half the latency of them. BCOS has already been used in over 300 different large-scale industrial scenarios and has become one of the most popular permissioned blockchains.

Broadcasting plays a vital role in the consensus mechanisms of blockchain systems, since the consensus of each block must wait until the previous block is received by (nearly) all the nodes in the blockchain systems. Therefore, optimizing the performance of broadcasting can significantly improve the performance of the blockchain system. However, compared with other traditional P2P applications such as file downloading or video delivery, the broadcasting in blockchain has two new requirements, namely low redundancy and low propagation latency, which all the existing mechanisms (e.g. flooding, structural DHT etc.) can not meet well. In this paper, we propose Swift, a new broadcasting mechanism for blockchain systems. It optimizes the P2P topology construction and broadcast algorithm in the structured network based on unsupervised learning and greedy algorithm, effectively reducing the propagation latency of the blockchain P2P network while avoiding the waste of redundant bandwidth. We implemented a prototype of Swift and evaluated its performance on a testbed network that consists of 1000 blockchain nodes. The experimental findings show that Swift can reduce propagation latency by 19.8% with similar bandwidth consumption, generating an 18% increase in the throughput performance of the blockchain. Finally, with the increase in connections, Swift can simultaneously achieve low latency and maintain a relatively stable redundant bandwidth waste, instead of linearly increasing in flooding.

The advances in wireless communications and mobile devices have resulted in a massive growth of the video services over mobile networks. In this article, we study the potential of peer-assisted video delivery in WiFi mobile networks aimed at reducing servers¿ load. Our study is based on a real measurement of mobile video viewing logs from a leading Internet video provider for 14 days. We analyze viewing behavior of users with respect to three main factors for the design of peer-assisted delivery network: viewing time, user population, and user locality. We then discuss the implications of the observations. Finally, we apply the findings on a BitTorrent-like VoD system and perform experiments with the collected viewing logs to demonstrate the benefits of peer-assisted video delivery. The peer assistance can reduce the servers¿ load by as much as 50 percent for popular videos on average.

In the Interplanetary File System (IPFS), consumers can help each other protect data against hardware failures and improve data availability through replication. While previous replication methods in peer-to-peer (P2P) networks can be used to increase data availability in the IPFS network, they are either hostile to peers with limited availability, preventing them from achieving adequate data availability, or lack flexibility. An ideal replication method should optimize data availability in a manner equitable to all peers while providing flexibility. To achieve this goal, this paper introduces a blockchain-based file replication mechanism. Leveraging the non-tamperable and traceable nature of blockchain technology, our mechanism achieves secure storage and trustworthy query of peers’ information used in the file replication process. Unlike most earlier methods, our mechanism employs an Arweave-inspired file replication algorithm that prioritizes the less available files within the system for replication until all files’ availabilities are optimized. Replicating files according to predefined system-wide cooperation rules like this not only limits the selfishness of peers but also facilitates timely adjustments in response to changes in the P2P system. In addition, our mechanism also uses smart contracts to judge and exclude dishonest peers, thereby fostering honest cooperation among peers without involving any third party.