Heterogeneity-Aware Erasure Codes for Peer-to-Peer Storage Systems

Peer-to-peer (P2P) storage systems rely on data redundancy to obtain high levels of data availability. Among the existing data redundancy schemes, erasure coding is a widely adopted scheme in existing P2P storage systems. By properly tunning its parameters, erasure codes can minimize the required data redundancy, which reduces both the storage and the network overheads. However, to perform this optimization, storage systems need to measured the obtained data availability. Existing P2P storage systems assume homogeneous node availabilities in order to simplify this measurement. As we will prove, this assumption entails efficiency losses when real node availabilities are highly heterogeneous. In this work, we analyze how erasure codes can be optimized in an availability-aware fashion. We propose an analytical framework able to measure data availability more precisely than existing works. As a result, we can optimize the erasure code deployment while reducing its associated overheads. Our experiments show how by considering real node availabilities it is possible to reduce data redundancy about 50% and up to 80% in some specific scenarios.