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Towards Efficient and Decentralized Spatial Crowdsourcing
PhD Thesis Proposal Defence Title: "Towards Efficient and Decentralized Spatial Crowdsourcing" by Mr. Mingzhe LI Abstract: With the proliferation of mobile devices, spatial crowdsourcing has emerged as a transformative system, where requesters outsource their spatio-temporal tasks to workers who are willing to perform the tasks at specified locations. However, existing spatial crowdsourcing usually suffers from the problem of centralization and limited efficiency. To address the above issues, we make the following contributions. First, we propose PriTA, a distributed spatial crowdsourcing framework which protects PRIvacy and achieves efficient Task Assignment. It protects workers’/tasks’ location privacy through homomorphic encryption. Novel wait-and-decide and proportional-backoff mechanisms are proposed to increase the number of assigned tasks. Second, a decentralized, secure, transparent and fair platform is essential for spatial crowdsourcing. The emergence of blockchain has made it possible. Requesters and workers can invoke smart contracts (functions executing various logic) in blockchain to handle task assignment and reward settlement without worrying about manipulation of assignment and settlement results. However, existing blockchain-based crowdsourcing systems generally suffer from the issue of lacking efficient task assignment schemes and the risk of losing requesters’/worker’ deposit. Thereby, we design SC-EOS, a blockchain-based spatial crowdsourcing framework. It frees users from deposits by linking every action for each user, and provides efficient and user-customizable task assignment via judicious smart contract modifications and design. Finally, a critical efficiency issue when applying blockchain to crowdsourcing is its poor scalability. Sharding is proposed to improve blockchain scalability, increasing throughput by partitioning nodes into multiple smaller groups. However, when tackling smart contracts, existing blockchain sharding protocols do not scale well. We therefore present Jenga, a novel sharding-based approach for efficient smart contract processing. It requires all shards share the logic for all contracts, so that smart contracts can be executed within one round. Moreover, different shards store distinct states (state shards), several "orthogonal" execution channels are established based on the state shards to reduce cross-shard communication. Date: Wednesday, 13 April 2022 Time: 3:00pm - 5:00pm Zoom Meeting: https://hkust.zoom.us/j/95006228325?pwd=OEtEQmtvbTVvNDdhTE12NWNrdXNZQT09 Committee Members: Dr. Wei Wang (Supervisor) Prof. Jin Zhang (Supervisor, SUSTech) Prof. Lei Chen (Chairperson) Prof. Gary Chan Prof. Bo Li **** ALL are Welcome ****