Geo-distributed consensus protocols provide high availability and resilience for distributed database services. These protocols group nodes by their data centers to leverage the network topology that spans across multiple data centers, thereby reducing costly cross-datacenter communication. However, they still face performance and scalability challenges due to inefficient log replication mechanisms. 1) These protocols rely on the leader node in each group to perform cross-datacenter log replication, creating a single-node performance bottleneck. 2) Byzantine receivers can behave arbitrarily, forcing the group leader to send multiple log copies during replication to prevent loss, thus causing redundant transmissions. 3) Since all groups must execute these logs in the same order, synchronizations across groups are necessary to maintain consistency when multiple groups are proposing concurrently, which also slow down log replication. This paper presents MassBFT, a Byzantine fault-tolerant geo-consensus protocol that achieves high performance and scalability. We design an encoded bijective log replication to eliminate the leader bottleneck and reduce the cross-datacenter network consumption. We also propose asynchronous log ordering to eliminate synchronization across groups. Experimental results show that MassBFT is scalable, fault-tolerant, and outperforms state-of-the-art protocols with 5.49-29.96 times higher throughput under YCSB, SmallBank, and TPC-C workloads.

Existing disaggregated databases separate execution and storage layers, enabling independent and elastic scaling of resources. In most cases, this design makes transaction concurrency control (CC) a critical bottleneck, which demands significant computing resources for concurrent conflict management and struggles to scale due to the coordination overhead for concurrent conflict resolution. Coupling CC with execution or storage limits performance and elasticity, as CC's resource needs do not align with the free scaling of the transaction execution layer or the storage-bound data layer. This paper proposes Concurrency Control as a Service (CCaaS), which decouples CC from databases, building an execution-CC-storage three-layer decoupled database, allowing independent scaling and upgrades for improved elasticity, resource utilization, and development agility. However, adding a new layer increases latency due to the shift in communication from hardware to network. To address this, we propose a Sharded Multi-Write OCC (SM-OCC) algorithm with an asynchronous log push-down mechanism to minimize network communications overhead and transaction latency. Additionally, we implement a multi-write architecture with a deterministic conflict resolution method to reduce coordination overhead in the CC layer, thereby improving scalability. CCaaS is designed to be connected by a variety of execution and storage engines. Existing disaggregated databases can be revolutionized with CCaaS to achieve high elasticity, scalability, and high performance. Results show that CCaaS achieves 1.02–3.11X higher throughput and 1.11–2.75X lower latency than SoTA disaggregated databases.

Blockchain serves as a replicated transactional processing system in a trustless distributed environment. Existing blockchain systems all rely on an explicit ordering step to determine the global order of transactions that are collected from multiple peers. The ordering consensus can be the bottleneck since it must be Byzantine-fault tolerant and can scarcely benefit from parallel execution. In this paper, we propose an ordering-free architecture that makes ordering implicit through deterministic execution. Based on this novel architecture, we develop a permissioned blockchain system NeuChain. A number of key optimizations such as asynchronous block generation and pipelining are leveraged for high throughput and low latency. Several security mechanisms are also designed to make our system robust to malicious attacks. Our geo-distributed experimental results show that NeuChain can achieve 47.2--64.1X throughput improvement over HyperLedger Fabric and 1.6--12.2X throughput improvement over the state-of-the-art high performance blockchains.