期刊
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
卷 152, 期 -, 页码 257-272出版社
ELSEVIER
DOI: 10.1016/j.future.2023.11.008
关键词
Decentralized systems; Decentralized search; Web3; Blockchain technology; Censorship resistance; Skip graph
DESCAN is a decentralized and censorship-resistant indexing and search engine for Web3 that allows storage and retrieval of Web3 transactions. It utilizes custom rules for indexing transactions and stores the generated triplets in a distributed transaction graph, enabling decentralized search. Four modifications are proposed to improve the system's robustness by enhancing the Skip Graph data structure. Experimental results demonstrate that DESCAN can tolerate adversarial and unresponsive peers without disruption. Searches in DESCAN are completed quickly, even as the network grows, and storage and network costs are evenly distributed among peers.
The popularity of blockchain technology has bootstrapped many Web3applications, e.g., Ethereum and IPFS, that apply distributed ledger technology to store transactions. The amount of transactions generated and stored in such Web3 applications is significant and, in its raw form, usually not searchable by users. Existing Web3 transaction indexing and search engines are predominantly centralized and, therefore, can manipulate search results or censor particular queries. With the proliferation of Web3 transactions and applications, a decentralized and censorship-resistant search primitive is becoming essential.We present DESCAN, a decentralized and censorship-resistant indexing and search engine for Web3. Users index their local Web3 transactions using custom rules that output triplets. Generated triplets are bundled in a distributed transaction graph that is searchable by other users. To coordinate search and distribute the storage of the transaction graph over peers in the network, we build upon a Skip Graph (SG) data structure. Since the Skip Graph does not provide any resilience against adversarial peers that censor searches, we propose four modifications to improve its robustness. We implement DESCAN and conduct experiments with up to 12 800 peers and 10 million Ethereum transactions. Our experiments show that DESCAN with our modifications enabled can tolerate 20% adversarial peers and 35% unresponsive peers without disruption. Moreover, we find that searches in DESCAN are usually completed well within a second, even when the network grows. Finally, we show that storage and network costs are evenly distributed amongst peers as the network grows.
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