Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113359
DC FieldValueLanguage
dc.contributorDepartment of Computing-
dc.creatorHong, Zicong-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/13579-
dc.language.isoEnglish-
dc.titleScaling blockchain via sharding-
dc.typeThesis-
dcterms.abstractAs a promising solution to blockchain scalability, sharding divides blockchain nodes into small groups called shards, splitting the workload. Existing works for sharding, however, are limited by three challenges. First, cross-shard transactions multiply the overhead of blockchain sharding, since the system needs to split each cross-shard transaction into multiple sub-transactions, each of which costs a consensus round to commit. Second, the independent and random scheduling for cross-shard transactions in different shards results in numerous conflicts and aborts since their involved accounts may be modified or locked by the others before they are committed. Third, for a blockchain database, a new and popular blockchain application, it is challenging to construct a scalable blockchain database through traditional on-chain sharding. Therefore, in chapter 3, we present a new blockchain sharding schema, named layered sharding, to improve the scalability via sharding while processing the cross-shard transactions efficiently. In chapter 4, we present PROPHET, a sharding blockchain system with deterministic ordering for conflict-free transactions. In chapter 5, we propose GrIDB, the first scalable blockchain database that distributes tables to different shards and provides efficient cross-shard database services. Evaluation of the real-world datasets for blockchain shows the remarkable performance improvement of our proposed systems over existing solutions.-
dcterms.accessRightsopen access-
dcterms.educationLevelPh.D.-
dcterms.extentxvii, 118 pages : color illustrations-
dcterms.issued2025-
dcterms.LCSHBlockchains (Databases)-
dcterms.LCSHComputer networks-
dcterms.LCSHElectronic data processing -- Distributed processing-
dcterms.LCSHHong Kong Polytechnic University -- Dissertations-
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