A simpler load-balancing algorithm for range-partitioned data in peer-to-peer systems

TL;DR

This paper introduces a simple, non-recursive load-balancing algorithm for range-partitioned peer-to-peer systems that maintains balanced loads while preserving key order, improving implementability over previous recursive methods.

Contribution

The authors propose a new non-recursive load-balancing algorithm that achieves comparable load ratio guarantees with simpler implementation in peer-to-peer networks.

Findings

Guarantees a max-min load ratio of 7.464 for insertions and deletions.

Uses constant amortized costs for load balancing operations.

Simplifies previous recursive algorithms for practical deployment.

Abstract

Random hashing is a standard method to balance loads among nodes in Peer-to-Peer networks. However, hashing destroys locality properties of object keys, the critical properties to many applications, more specifically, those that require range searching. To preserve a key order while keeping loads balanced, Ganesan, Bawa and Garcia-Molina proposed a load-balancing algorithm that supports both object insertion and deletion that guarantees a ratio of 4.237 between the maximum and minimum loads among nodes in the network using constant amortized costs. However, their algorithm is not straightforward to implement in real networks because it is recursive. Their algorithm mostly uses local operations with global max-min load information. In this work, we present a simple non-recursive algorithm using essentially the same primitive operations as in Ganesan {\em et al.}'s work. We prove that for insertion and deletion, our algorithm guarantees a constant max-min load ratio of 7.464 with constant amortized costs.