Parallelized In-Network Aggregation for Failure Repair in Erasure-Coded Storage Systems

To repair a failed block in the erasure-coded storage system, multiple related blocks have to be retrieved from other storage nodes across the network. Such a process can lead to significant incast-type repair traffics and delays. The existing efforts mainly try to schedule the transmission of the requested blocks across different storage nodes to avoid network congestion. At their cores, they utilize part of the involved hosts to rely on or aggregate the file blocks from others. While we notice that, the programmability and capability of today's network devices (i.e., routers and switches) bring a great opportunity to further speed up the repair progress by aggregating the file blocks with such devices. By mitigating the aggregation operations from the network edges to network cores, it is possible to save more time and bandwidth. With this intuition, we propose Paint, a parallelized in-network aggregation framework for failure repair. Paint utilizes programmable switches to aggregate relevant data and improves the repair performance by implementing multiple parallelized repair pipelines. We propose a series of novel and time-friendly algorithms to construct the routing paths for Paint and design the Aggregation Control Protocol to implement Paint in production clusters. For all we know, this is the first work to explore and implement parallelized in-network repair with programmable switches. The extensive experiments on the prototype system and real-world datasets indicate that Paint can significantly improve repair performance while effectively reducing bandwidth overhead.