- The paper's main contribution is an optimistic commit protocol that achieves strong consistency with a single round-trip commit in multi-data center environments.
- It leverages Generalized Paxos to enable commutative updates and masterless coordination, significantly reducing latency compared to traditional two-phase commit protocols.
- Evaluation on Amazon EC2 with the TPC-W benchmark shows MDCC nearly doubles throughput and robustly handles data center failures.
Overview of MDCC: Multi-Data Center Consistency
The paper "MDCC: Multi-Data Center Consistency" introduces a novel approach to achieving strong consistency across distributed data centers, a task that traditionally incurs high latency and complexity. The authors propose MDCC—an innovative optimistic commit protocol that leverages concepts from distributed consensus algorithms, particularly Generalized Paxos, to provide the benefits of strong consistency with the performance characteristics usually associated with eventually consistent systems.
Key Contributions and Methodology
The primary contribution of the paper is the development of an optimistic commit protocol capable of enforcing strong consistency across multiple data centers without a central coordinator. MDCC does so by using a single round-trip in the typical operational scenario. This capability distinguishes MDCC from conventional protocols like two-phase commit (2PC), which suffer from inefficiencies due to the necessity of a coordinator and multiple communication rounds.
The authors draw on Generalized Paxos to allow commutative updates, which permit nodes to accept proposals out of order, thus reducing unnecessary conflicts and improving throughput. This innovative combination allows MDCC to bypass a master node by using fast rounds, wherein proposals are directly submitted to storage nodes rather than routed through a centralized master. This significantly enhances performance by reducing latency.
MDCC is capable of handling network delays and data center outages robustly. Through an integration with a novel programming model, application developers can manage the unpredictable nature of network-induced latency by defining service-level objectives (SLOs). The model facilitates a structured way to provide end-user feedback dependent on the progress of transaction commits.
Evaluation and Results
The implementation of MDCC was tested across multiple geographically distributed Amazon EC2 data centers, using the TPC-W benchmark—a standardized workload that simulates an e-commerce environment. The results affirm MDCC's capacity to deliver transaction latencies and throughputs comparable to quorum-based, eventually consistent systems, but with the added guarantee of strong consistency and resilience to data center failures.
The experiments reveal that MDCC achieves a reduction in latency by approximately 50% compared to conventional 2PC protocols, with throughput nearly doubling, indicative of significant performance gains. Furthermore, the system maintains performance close to eventually consistent quorum protocols despite offering stronger consistency guarantees.
Implications and Future Directions
The practical implications of MDCC are substantial, notably for organizations that require globally distributed databases with stringent consistency requirements, yet cannot compromise on latency. MDCC's protocol design inherently accommodates fault tolerance, which is critical in modern cloud and distributed environments.
Theoretically, the paper advances the understanding of how consensus algorithms like Generalized Paxos can be extended and optimized for broad, real-world applications. The introduction of masterless coordination and the exploitation of commutative operations set a precedent for future distributed systems aiming to balance consistency and performance.
Looking forward, future research could explore the integration of MDCC with other isolation levels or distributed programming models, potentially broadening its applicability. Moreover, optimizing the fast vs. classic round strategies based on dynamic workload analysis presents another opportunity for enhancing MDCC's efficiency. Additionally, expansion into different languages and environments could further support adoption and industrial application.
Overall, MDCC represents a significant step toward reconciling the trade-offs between consistency, availability, and partition tolerance in distributed multi-data center environments. With its innovative design and encouraging benchmark results, MDCC sets a promising foundation for future advancements in distributed data systems.