This project involves designing and implementing a new system, called Peer-to-peer Database (P2PDB), that will serve as a decentralized platform for data publishing, sharing, and querying of data. P2PDB enables an unlimited number of independent participants to publish and access the contents of datasets stored across the participants. The system will provide decentralized publishing and querying functionality over structured data in an analogous fashion to how the "world wide web" enables decentralized publishing and accessing of unstructured data. However, P2PDB differs from both the traditional world wide web (and also other attempts at building peer-to-peer structured database systems) in the way that it provides incentives for performing tasks that are critical to the well-being of the system as a whole, including contribution, integration, storing, and processing of data, and enforcing good behavior by the participants. This project includes involvement in the research track at "Technica," the largest all-female hackathon in the US hosted every year at the University of Maryland, and computer science curricular development at the local high school level.

The project includes working on several challenging research problems that result from an architectural assumption that any entity may participate in the storage and processing of data in P2PDB. First, the system must be robust in the face of malicious nodes that join the system and intentionally corrupt data or return incorrect results upon receiving a query. This requires research effort in the areas of query verification, secure data processing, and decentralized dispute moderation. Another important research problem that emerges from the planned architecture of P2PDB is query optimization and execution over a federated architecture in which queries must be performed across many different entities, each with different service level guarantees and costs.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
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Wei-Shinn Ku
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University of Maryland College Park
College Park
United States
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