Related papers: Lion: Minimizing Distributed Transactions through …
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…
We investigate a decentralised approach to committing transactions in a replicated database, under partial replication. Previous protocols either re-execute transactions entirely and/or compute a total order of transactions. In contrast,…
DGCC protocol has been shown to achieve good performance on multi-core in-memory system. However, distributed transactions complicate the dependency resolution, and therefore, an effective transaction partitioning strategy is essential to…
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…
With the advent of the Internet and Internet-connected devices, modern business applications can experience rapid increases as well as variability in transactional workloads. Database replication has been employed to scale performance and…
The Lion optimizer has been a promising competitor with the AdamW for training large AI models, with advantages on memory, computation, and sample efficiency. In this paper, we introduce Distributed Lion, an innovative adaptation of Lion…
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…
Distributed transactions on high-overhead TCP/IP-based networks were conventionally considered to be prohibitively expensive and thus were avoided at all costs. To that end, the primary goal of almost any existing partitioning scheme is to…
In order to increase availability in a distributed system some or all of the data items are replicated and stored at separate sites. This is an issue of key concern especially since there is such a proliferation of wireless technologies and…
Transaction scheduling is crucial to efficiently allocate shared resources in a conflict-free manner in distributed systems. We investigate the efficient scheduling of transactions in a network of fog-cloud computing model, where…
A new type of logs, the command log, is being employed to replace the traditional data log (e.g., ARIES log) in the in-memory databases. Instead of recording how the tuples are updated, a command log only tracks the transactions being…
We address the problem of content replication in large distributed content delivery networks, composed of a data center assisted by many small servers with limited capabilities and located at the edge of the network. The objective is to…
A new emerging class of parallel database management systems (DBMS) is designed to take advantage of the partitionable workloads of on-line transaction processing (OLTP) applications. Transactions in these systems are optimized to execute…
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…
A working implementation of nested transactions has been produced for LOCUS, an integrated distributed operating system which provides a high degree of network transparency. Several aspects of our mechanism are novel. First, the mechanism…
Replicated tree data structures are extensively used in collaborative applications and distributed file systems, where clients often perform move operations. Local move operations at different replicas may be safe. However, remote move…
Communication overhead is a key challenge in distributed deep learning, especially on slower Ethernet interconnects, and given current hardware trends, communication is likely to become a major bottleneck. While gradient compression…
Increasing need for large-scale data analytics in a number of application domains has led to a dramatic rise in the number of distributed data management systems, both parallel relational databases, and systems that support alternative…
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…
With the widespread use of shared-nothing clusters of servers, there has been a proliferation of distributed object stores that offer high availability, reliability and enhanced performance for MapReduce-style workloads. However, relational…