Xuanye Zhu

dblp:428/4072 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0002-5230-2409ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 since 2021Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
2 papers
Distributed systems · 77% Parallel and multicore computing · 23%
Network and information security
2 papers
Blockchain and cryptocurrency security · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems
consensus
1.322026
CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol · IEEE Trans. Serv. Comput. 2026
ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards · IEEE Trans. Netw. 2026
Blockchain and cryptocurrency security
blockchain interoperability
1.012026
CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol · IEEE Trans. Serv. Comput. 2026
Blockchain and cryptocurrency security › blockchain scalability
blockchain sharding
1.012026
ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards · IEEE Trans. Netw. 2026
Blockchain and cryptocurrency security › blockchain scalability › blockchain sharding
cross-shard transaction
1.012026
ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards · IEEE Trans. Netw. 2026
Distributed systems › consensus
committee election
1.012026
CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol · IEEE Trans. Serv. Comput. 2026
Parallel and multicore computing
load balancing
1.012026
ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards · IEEE Trans. Netw. 2026
Distributed systems › distributed database
sharding
1.012026
ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards · IEEE Trans. Netw. 2026
Virtual and augmented reality
metaverse
0.312026
CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol · IEEE Trans. Serv. Comput. 2026

Methods — techniques the papers use, named apart from their topics

smart contract · 3.0nash equilibrium · 3.0availability proofs · 3.0network partitioning · 2.0community detection · 2.0account migration · 2.0
YearPublicationVenuePosition
2026 ShardCutter: A Blockchain Sharding Protocol Achieving Transaction Workload Balance Across State Shards
abstract
Blockchain sharding has been deemed a promising solution that can substantially improve blockchain scalability. However, developers must overcome two major technical challenges to implement a sharded blockchain. The first challenge is the high cross-shard transaction ratio in blockchain shards. This issue significantly degrades the throughput of a sharded blockchain. The second challenge is the imbalanced workloads across blockchain shards. In a blockchain with imbalanced workloads, some busy shards have to handle an overwhelming number of transactions and thus become congested. Facing these two challenges, a dilemma is that it is difficult to guarantee a lowcross-shard transaction ratioand maintain thebalanced workloadsacross all shards, simultaneously. We believe that a fine-grained account allocation strategy can address this dilemma. To this end, we formulate the tradeoff between these two metrics as a network-partition problem. We then solve this problem by proposing a sharding protocol, namedShardCutter, which includes the following two crucial components: a community-aware account partition algorithm and a fine-tuned account migration mechanism. Finally, experimental results demonstrate that the proposed protocol outperforms other baselines in terms of throughput, makespan, cross-shard transaction ratio, and the workload balance of shards’ transaction pool.
Huawei Huang, Xuanye Zhu, Ting Cai 0002, Lu Zhou 0002, Zibin Zheng, Song Guo 0001
IEEE Trans. Netw.3
2026 CrossMeta: A Fast and Cheap Cross-Metaverse Interoperability Protocol
abstract
Metaverse is drawing increasing attention from both academia and industry. Interoperability among different metaverse systems has become essential. A cross-metaverse interoperability protocol can enable interoperability across metaverses. However, cross-metaverse protocols often suffer significant cost overhead and transaction latency. For example, in STYLE, a leading cross-metaverse platform, 74% of transaction latency and 97% of the cost overhead are attributed to the relay blockchain rather than the two participating metaverses. To make cross-metaverse efficient, in this paper, we propose a fast and cheap cross-metaverse interoperability protocol namedCrossMeta.CrossMetacan enable direct communication among heterogeneous metaverses rather than depending on a relay blockchain. This is achieved through two components: i) a committee that relays transactions from the source metaverse to the destination metaverse, along with availability proofs, and ii) a smart contract that verifies the proofs provided by the committee. To ensure an honest majority within the selected committee, we propose a dynamic committee selection method based on the chain quality property. Furthermore, we demonstrate that honest brokers achieve a Nash equilibrium. Additionally, we prove that the proposedCrossMetaprotocol satisfies the security properties of atomicity and liveness. To demonstrate the practicality ofCrossMeta, we implemented a prototype of theCrossMetausing two real-world metaverse platforms, i.e.,Axie InfinityandSandbox. The evaluation results show thatCrossMetaoutperforms other cross-metaverse solutions regarding transaction latency and gas fees.
Taotao Li, Qinglin Yang, Huawei Huang, Xuanye Zhu, Zhu Sun 0001, Yuan Liu 0002, Zibin Zheng
IEEE Trans. Serv. Comput.4