WiseCode: Breaking the Scalability Barriers of Wide-Stripe Vector Codes

Wide-stripe erasure codes, with tens to over a hundred data chunks per stripe, offer high reliability at low storage overhead. Existing wide-stripe designs that are based on scalar codes (e.g., LRCs in Google and Azure) reduce repair traffic but increase storage overhead . Although vector codes are theoretically optimal in both metrics, they face severe scalability barriers in wide-stripe deployments. We present WiseCode, the first practical and scalable wide-stripe vector-coding approach that achieves both efficient repair and ultra-low storage overhead. WiseCode overcomes three key scalability barriers through innovations in coding structure, coefficient selection, and coding algorithms. It introduces a template-unfold structure design that avoids sub-packetization blowup, a repetition-minimized search strategy that reduces coefficient search cost, and a two-stage coding algorithm that enables efficient encoding and decoding. Evaluations on Ceph with ∼100-wide stripes and 1.04–1.06 storage overhead show that WiseCode increases repair throughput by 1.41×–2.18× compared to Google’s UCLRCs at equal storage overhead, and also delivers higher throughput even at 2% lower storage overhead. WiseCode retains this advantage when combined with advanced repair-scheduling methods, consistently outperforming UCLRCs.