Towards General-Purpose Decentralized Computing with Permissionless Extensibility
Enis Ceyhun Alp
Ph.D. thesis advised by Bryan Ford
January 19, 2024
Abstract:
Smart contracts have emerged as the most promising foundations for applications
of the blockchain technology. Even though smart contracts are expected to serve
as the backbone of the next-generation web, they have several limitations that
hinder their widespread adoption, namely limited computational functionality,
restricted programmability, and lack of data confidentiality. Moreover,
addressing these challenges manually in application-specific ways requires a
lot of developer effort and time due to the monolithic architecture of smart
contracts. In this dissertation, we start over with a novel architecture for
building and deploying general-purpose decentralized programs. To this end, we
first propose a new architecture that replaces the monolithic execution model
of smart contracts with a modular one to support a rich set of functionality,
which can be easily and permissionlessly extended at any time. Second, to
support the efficient deterministic execution required by
computationally-advanced smart contracts, we build a deterministic sandbox with
floating-point arithmetic support that brings safe and deterministic execution
together with general-purpose programming without having to sacrifice
performance. Finally, we combine threshold cryptography and the blockchain
technology to build a framework that enables mutually distrustful parties to
share their confidential data in a fully auditable, transparent and
decentralized manner. Through prototyping and evaluation using real-world
applications, we demonstrate that it is possible and feasibly-practical to
build a decentralized computing platform that can support general-purpose
computations.