{"id":896829,"date":"2022-11-08T15:31:13","date_gmt":"2022-11-08T23:31:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/"},"modified":"2022-11-08T15:31:13","modified_gmt":"2022-11-08T23:31:13","slug":"hydra-serialization-free-network-ordering-for-strongly-consistent-distributed-applications","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/hydra-serialization-free-network-ordering-for-strongly-consistent-distributed-applications\/","title":{"rendered":"Hydra: Serialization-Free Network Ordering for Strongly Consistent Distributed Applications"},"content":{"rendered":"<div class=\"row\">\n<div class=\"col datacolumn\">\n<div class=\"pub-details\">\n<div class=\"abstract well\" data-ex-content=\".abstract\">A large class of distributed systems, e.g., state machine replication and fault-tolerant distributed databases, rely on establishing a consistent order of operations on groups of nodes in the system. Traditionally, an application-level distributed protocol such as Paxos and two-phase locking provide the ordering guarantees. To reduce the performance overhead imposed by these protocols, a recent line of work propose to move the responsibility of ensuring operation ordering into the network by sequencing requests through a centralized network sequencer. This network sequencing approach yields significant application-level performance improvements, but routing all requests through a single sequencer comes with several fundamental limitations, including sequencer scalability bottleneck, prolonged system downtime during sequencer failover, worsened network-level load balancing, etc.Our work, Hydra, overcomes these limitations by using a distributed set of network sequencers to provide network ordering. Hydra leverages loosely synchronized clocks on network sequencers to establish message ordering across them, per-sequencer sequence numbers to detect message drops, and periodic timestamp messages to enforce progress when some sequencers are idle. To demonstrate the benefit of Hydra, we co-designed a state machine replication protocol and a distributed transactional system using the Hydra network primitive. Compared to serialization-based network ordering systems, Hydra shows equivalent performance improvement over traditional approaches in both applications, but with significantly higher scalability, shorter sequencer failover time, and better network-level load balancing.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>A large class of distributed systems, e.g., state machine replication and fault-tolerant distributed databases, rely on establishing a consistent order of operations on groups of nodes in the system. Traditionally, an application-level distributed protocol such as Paxos and two-phase locking provide the ordering guarantees. To reduce the performance overhead imposed by these protocols, a recent 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