https://blog.mickeyzzc.tech/en/tags/failure-detection/Recent content in Failure Detection on Mi&Bee BlogHugo -- gohugo.ioen蓝宝石的傻话Tue, 07 Jul 2026 00:00:00 +0000https://blog.mickeyzzc.tech/en/posts/network/gossip-protocol-theory/Tue, 07 Jul 2026 00:00:00 +0000https://blog.mickeyzzc.tech/en/posts/network/gossip-protocol-theory/<p>In P2P networks, every node needs to learn the global cluster state—which peers are online, where data is stored, and whether new nodes have joined or old ones left—without relying on any central server. The essence of this problem is: <strong>how can information be disseminated efficiently and reliably across an unpredictable, dynamic network?</strong></p> <p>Gossip protocol (also called Epidemic protocol) offers an elegant answer: mimic the spread pattern of infectious diseases. Each node randomly selects several neighbors and exchanges the information it knows. The message spreads like a virus, eventually reaching all nodes with high probability. It requires no centralized coordinator and has natural tolerance for network partitions and node failures.</p>https://blog.mickeyzzc.tech/en/posts/network/swim-membership-protocol/Tue, 07 Jul 2026 00:00:00 +0000https://blog.mickeyzzc.tech/en/posts/network/swim-membership-protocol/<p>In the previous article, we explored the core principles of the Gossip protocol in depth—Epidemic propagation models, the distinction between Anti-Entropy and Rumor-Mongering, and the mathematical foundation of the Phi Accrual failure detector. Gossip provides a general mechanism for information dissemination, but to build a complete distributed cluster, information dissemination alone is not enough: <strong>every node needs to know who else is in the cluster—who is online, who has left, and who has just joined.</strong></p>