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Chen, Yuling, Yin, Hongyan, Xiang, Yuexin, Ren, Wei, Ren, Yi 
ORCID: https://orcid.org/0000-0001-7423-6719 and Xiong, Neal Naixue
(2020)
CVT: A crowdsourcing video transcoding scheme based on blockchain smart contracts.
IEEE Access, 8.
pp. 220672-220681.
ISSN 2169-3536
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Abstract
Streaming media has been largely used by millions of users every day. The number of customers and programs, e.g., TV series, movies, and various shows, are still growing fast. However, the demand for video transcoding for various personal terminal devices results in the shortage of computing resources and the prolongation of processing delay in centralized video transcoding systems. To solve this issue, we propose a blockchain, especially, smart contract based scheme that can achieve decentralized and on-demand crowdsourcing for video transcoding, which remarkably mitigates the transcoding overhead. Specifically, our scheme consists of four key components such as employers, workers, task allocation, and payment. An employer initializes the smart contract, releases the task, and initiates the smart contract. Workers bid for the task, and the successful bidder will obtain the task and execute the task. The task allocation mechanism and the payment mechanism can guarantee the profits of both and encourage both as well. Moreover, the smart contract consists of the bidding contract and the task execution contract. The extensive analysis of our proposed scheme justified the feasibility, security for defending against typical threats, applicability in realistic situations, and portability for most multimedia such as videos and audios.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | blockchain,crowdsourcing,smart contracts,video transcoding,computer science(all),materials science(all),engineering(all) ,/dk/atira/pure/subjectarea/asjc/1700 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 08 Jan 2021 01:07 |
| Last Modified: | 10 Dec 2024 01:36 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/78115 |
| DOI: | 10.1109/ACCESS.2020.3043042 |
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