ResNetLab | Protocol Labs Research
ResNetLab
A resilient system or network is fundamentally uncompromised by an isolated failure or network split. The system is malleable, adaptable to different conditions and capable of evolving to meet new requirements over time. That said, resilience here identifies also as a characteristic against changing system or network conditions, i.e., the system’s core operating principles adjust so that performance remains when the system scales up to serve increasing demand from more users. Building resilience into foundational infrastructure is the key in building a computing and networking fabric for human knowledge.
Mission & Vision
The mission of the Resilient Networks Lab is to build resilient distributed systems, by creating and operating a platform where researchers can collaborate openly and asynchronously on deep technical work.
Motivation & Description
The lab’s genesis comes from a need present in the IPFS and libp2p projects to amp their research efforts to tackle the critical challenges of scaling up networks to planet scale and beyond. The Lab is designed to take ownership of the earlier stages on the research pipeline, from ideas to specs and to code.
Research Endeavours
- Decentralized Data Delivery Markets (3DMs): A fully permissionless market for data delivery that supports fair data exchange on the service provided.
- Networking in Heterogeneous Runtimes: Leveraging computational resources outside of the cloud to perform computations closer to data sources.
- Preserve users’ privacy when providing and fetching content: Ensuring that IPFS users can collect and provide information while maintaining their full anonymity.
- Mutable data (naming, real-time, guarantees): Defining essential primitives for dynamic applications in the Distributed Web.
- Human-readable naming: Exploring Zooko’s Trilemma and potential resolutions with contextual data.
- Enhanced bitswap/graphsync with more network smarts: Improving bitswap protocol performance.
- Routing at scale (1M, 10M, 100M, 1B.. nodes): Addressing routing scalability in content-addressable networks.
- PubSub at scale (1M, 10M, 100M, 1B.. nodes): Preparing for significant performance challenges as the IPFS system grows.
- Improved layouts to represent data in hash-linked graphs (using IPLD): Optimizing data representation for enhancing file fetch times and performance.
Team
Publications
2022-11-07/Journal article
2021-06-21/Conference paper
2021-06-21/Conference paper
2021-06-11/Conference paper
2021-01-14/Report
Talks
- IPFS-FAN: A function addressible computation network - 2021-08-02
- Beyond swapping bits - 2021-02-23