Hermes: a Fast, Fault-Tolerant and Linearizable Replication Protocol (2001.09804v1)

Abstract: Today's datacenter applications are underpinned by datastores that are responsible for providing availability, consistency, and performance. For high availability in the presence of failures, these datastores replicate data across several nodes. This is accomplished with the help of a reliable replication protocol that is responsible for maintaining the replicas strongly-consistent even when faults occur. Strong consistency is preferred to weaker consistency models that cannot guarantee an intuitive behavior for the clients. Furthermore, to accommodate high demand at real-time latencies, datastores must deliver high throughput and low latency. This work introduces Hermes, a broadcast-based reliable replication protocol for in-memory datastores that provides both high throughput and low latency by enabling local reads and fully-concurrent fast writes at all replicas. Hermes couples logical timestamps with cache-coherence-inspired invalidations to guarantee linearizability, avoid write serialization at a centralized ordering point, resolve write conflicts locally at each replica (hence ensuring that writes never abort) and provide fault-tolerance via replayable writes. Our implementation of Hermes over an RDMA-enabled reliable datastore with five replicas shows that Hermes consistently achieves higher throughput than state-of-the-art RDMA-based reliable protocols (ZAB and CRAQ) across all write ratios while also significantly reducing tail latency. At 5% writes, the tail latency of Hermes is 3.6X lower than that of CRAQ and ZAB.

• The paper introduces Hermes, a replication protocol that delivers high throughput and low latency with linearizable writes.
• Hermes uses logical timestamps and invalidation-based locking to enable decentralized, fault-tolerant operations.
• Evaluations reveal that Hermes outperforms protocols like ZAB and Derecho through single round-trip writes and improved tail latency.

Analysis of "Hermes: A Fast, Fault-Tolerant and Linearizable Replication Protocol"

The academic paper presented outlines Hermes, a novel replication protocol designed for high-performance datastores. This protocol is particularly relevant for environments demanding both high availability and strong consistency, such as in-memory databases deployed in modern data centers. Hermes aims to efficiently balance latency and throughput by allowing for local reads and leveraging a unique combination of invalidation mechanisms and logical timestamps to ensure linearizable writes.

Technical Overview

Hermes is built on a broadcast-based mechanism allowing for local reads at any replica while ensuring that write operations are efficiently managed. This is accomplished by enabling any replica to initiate a write, thus supporting inter-key concurrency and decentralization. The protocol circumvents the need for a central serialization point which is typically a bottleneck in many existing protocols, thereby reducing network hops and improving load distribution.

One of the distinguishing features of Hermes is its use of logical timestamps, inspired by Lamport clocks, which offer a robust means to manage the order of operations without a central coordinator. By embedding these timestamps directly into operations, Hermes allows for precise linearization of writes, ensuring that all replicas maintain a consistent state. Furthermore, invalidation-based locking inspired by cache coherence protocols assists in conflict resolution, allowing concurrent operations on the same key to be managed locally and efficiently.

Performance and Reliability

The protocol's performance is notable, with Hermes achieving both higher throughput and lower latency compared to contemporary standards like ZAB and CRAQ. For instance, the Hermes protocol typically completes writes in a single round-trip, showcasing marked improvements in tail latency, particularly in write-heavy workloads. The paper’s evaluation indicates that Hermes significantly outperforms existing RDMA-enabled systems such as Derecho, showing an order-of-magnitude improvement in throughput for small object sizes.

Moreover, Hermes has built-in fault tolerance mechanisms; operations, such as write replays, can handle node or network failures gracefully without compromising linearizability. By ensuring that all writes are safely replayable, Hermes addresses the potential pitfalls of message loss, failed acknowledgments, and node downtimes commonly observed in distributed systems.

Practical Implications and Future Directions

Practically, Hermes is positioned as an ideal solution for environments where low-latency access and high failure resilience are paramount. This is particularly relevant for applications in cloud environments and interactive services where performance consistency and fault tolerance directly impact user experience.

The theoretical groundwork laid by Hermes opens up several avenues for future research. With the increasing integration of hardware support such as RDMA and programmable networks, Hermes could be further refined to exploit these technologies, enhancing its scalability and operational efficiency. Additionally, while Hermes is optimized for single-key operations, an extension towards reliable multi-key transactional support could broaden its applicability to more complex distributed data applications.

In conclusion, the Hermes replication protocol provides a significant contribution to distributed datastore systems, effectively balancing the trade-offs between consistency, availability, and partition tolerance while achieving higher performance metrics than its predecessors. As distributed systems continue to evolve, protocols like Hermes will be integral in meeting the growing demands of scalability, reliability, and robustness in data-intensive applications.