Local Rendezvous Hashing: Bounded Loads and Minimal Churn via Cache-Local Candidates

Consistent hashing is fundamental to distributed systems, but ring-based schemes can exhibit high peak-to-average load ratios unless they use many virtual nodes, while multi-probe methods improve balance at the cost of scattered memory accesses. This paper introduces Local Rendezvous Hashing (LRH), which preserves a token ring but restricts Highest Random Weight (HRW) selection to a cache-local window of C distinct neighboring physical nodes. LRH locates a key by one binary search, enumerates exactly C distinct candidates using precomputed next-distinct offsets, and chooses the HRW winner (optionally weighted). Lookup cost is O(log|R| + C). Under fixed-topology liveness changes, fixed-candidate filtering remaps only keys whose original winner is down, yielding zero excess churn. In a benchmark with N=5000, V=256 (|R|=1.28M), K=50M and C=8, LRH reduces Max/Avg load from 1.2785 to 1.0947 and achieves 60.05 Mkeys/s, about 6.8x faster than multi-probe consistent hashing with 8 probes (8.80 Mkeys/s) while approaching its balance (Max/Avg 1.0697). A microbenchmark indicates multi-probe assignment is dominated by repeated ring searches and memory traffic rather than probe-generation arithmetic.