Ensuring data reliability in P2P networks: Strategies for success
November 24, 2022

Ensuring data reliability in P2P networks: Strategies for success

Understanding system reliability and the role of redundancy

The reliability of a system, such as its Mean Time Between Failures (MTBF), is often calculated by aggregating the reliability of its components. However, relying on intermittent or unreliable elements may not be the best idea for building a dependable service. Critical systems that cannot afford failure, like airplanes or spacecraft, are constructed with redundancy in mind—duplicating critical components to enhance reliability.

The benefits of peer-to-peer systems

Peer-to-peer (P2P) systems consist of thousands or millions of similar peers, which may be unreliable but easily duplicated. Simple duplication can be costly, requiring a file to be duplicated on multiple peers for increased availability. Thankfully, more optimal strategies exist for ensuring reliability in P2P networks:

Utilizing forward error correction in P2P storage

Error correction codes, such as Reed Solomon coding, were designed in the 1950s to control and repair errors in noisy communication channels. Redundancy is added to the transmitted information through additional data. RAID-6 for disk drives employs similar redundancy strategies.

In Hive's P2P file storage system, hiveDisk, files are split into shards of data distributed across the P2P network. Additional shards are created to account for disappearing peers or content destroyed by hardware failures. For example, 100 encrypted shards generated from your file and sent to 100 peers may only require 70 to rebuild the original file. Missing shards are regenerated when peers leave. With only 30% overhead, the probability of not being able to access the content is significantly lower compared to simple replication.

Modeling node behaviors for optimal data distribution

Peers in Hive's P2P network have the same role but exhibit different behaviors. Usage patterns and availability vary throughout the day, between peers, and across geographies. Hive learns each peer's behavior and optimally places each shard to ensure data can always be reconstructed when needed.

Ensuring data persistence in P2P networks

While forward error correction can mitigate unavailable peers, some peers may experience permanent hardware failures. Peers that haven't connected for a long time or fail to prove they have valid data are marked as failed peers. Hive's P2P network will start reconstructing its data elsewhere.

In conclusion, P2P networks can guarantee data availability in a heterogeneous, rapidly evolving group of peers by leveraging various strategies. Utilizing the advantage of numbers, these networks provide statistical cloud storage, ensuring data reliability and availability.