相关论文: Chiller: Contention-centric Transaction Execution …

The common wisdom is that distributed transactions do not scale. But what if distributed transactions could be made scalable using the next generation of networks and a redesign of distributed databases? There would be no need for…

Research in transaction processing has made significant progress in improving the performance of multi-core in-memory transactional systems. However, the focus has mainly been on low-contention workloads. Modern transactional systems…

Many distributed storage systems are transactional and a lot of work has been devoted to optimizing their performance, especially the performance of read-only transactions that are considered the most frequent in practice. Yet, the results…

A common approach to scaling transactional databases in practice is horizontal partitioning, which increases system scalability, high availability and self-manageability. Usu- ally it is very challenging to choose or design an optimal…

Blockchain uses the idea of storing transaction data in the form of a distributed ledger wherein each node in the network stores a current copy of the sequence of transactions in the form of a hash chain. This requirement of storing the…

In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a single-node non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to…

Distributed transaction processing often involves multiple rounds of cross-node communications, and therefore tends to be slow. To improve performance, existing approaches convert distributed transactions into single-node transactions by…

OLTP applications with high workloads that cannot be served by a single server need to scale out to multiple servers. Typically, scaling out entails assigning a different partition of the application state to each server. But data…

Traditional public distributed ledgers have not been able to scale-out well and work efficiently. Sharding is deemed as a promising way to solve this problem. By partitioning all nodes into small committees and letting them work in…

Most modern data stores tend to be distributed, to enable the scaling of the data across multiple instances of commodity hardware. Although this ensures a near unlimited potential for storage, the data itself is not always ideally…

To process a large volume of data, modern data management systems use a collection of machines connected through a network. This paper looks into the feasibility of scaling up such a shared-nothing system while processing a compute- and…

Modern database clusters entail two levels of networks: connecting CPUs and NUMA regions inside a single server in the small and multiple servers in the large. The huge performance gap between these two types of networks used to slow down…

Throughput limitations of existing blockchain architectures are one of the most significant hurdles for their wide-spread adoption. Attempts to address this challenge include layer-2 solutions, such as Bitcoin's Lightning or Ethereum's…

Although blockchains have become widely popular for their use in cryptocurrencies, they are now becoming pervasive as more traditional applications adopt blockchain to ensure data security. Despite being a secured network, blockchains have…

The excessively increased volume of data in modern data management systems demands an improved system performance, frequently provided by data distribution, system scalability and performance optimization techniques. Optimized horizontal…

Although significant recent progress has been made in improving the multi-core scalability of high throughput transactional database systems, modern systems still fail to achieve scalable throughput for workloads involving frequent access…

With the growing cyber-security threats, ensuring the security of data in Cloud data centers is a challenging task. A prominent type of attack on Cloud data centers is data tampering attack that can jeopardize the confidentiality and the…

Sharding has shown great potential to scale out blockchains. It divides nodes into smaller groups which allow for partial transaction processing, relaying and storage. Hence, instead of running one blockchain, we will run multiple…

Managing the transactions in real time distributed computing system is not easy, as it has heterogeneously networked computers to solve a single problem. If a transaction runs across some different sites, it may commit at some sites and may…

Disaggregated memory (DM) separates compute and memory resources, allowing flexible scaling to achieve high resource utilization. To ensure atomic and consistent data access on DM, distributed transaction systems have been adapted, where…