GeoLM: Performance-oriented Leader Management for Geo-Distributed Consensus Protocol

Duling Xu, Dafang Zhang, Tong Li, Yunpeng Chai, Zegang Sun, Weiming Li, Yangfan Liu, Qipeng Wang, Jiaqi Liang, Yang Ren, Wei Lu, Xiaoyong Du

Abstract: The global business of transnational enterprises demands geo-distributed databases, where the leader-follower-based consensus protocols are the key to guaranteeing consistency of replicas spread across regions. Compared with traditional databases running in a single data center, determining which node is the leader in consensus protocol has a greater per-formance impact in geo-distributed databases running across multiple data centers. However, the performance of legacy leader management is far from satisfactory due to the network and application dynamics (e.g., network delay, node popularity, operation read-write ratio). This paper proposes GeoLM toward performance-oriented leader management for geo-distributed consensus protocols. GeoLM captures the network and application dynamics and proactively conducts seamless leader handovers with bounded switching costs. Our geo-distributed experimental results show that GeoLM improves performance up to 49.75% over the baselines (e.g., Raft and Geo-Raft) and achieves considerably good performance compared to state-of-the-art consensus protocols (e.g., SwiftPaxos, CURP, and EPaxos).

External IDs:dblp:conf/infocom/XuZLCSLLWLRLD25