Modern distributed key-value (KV) stores adopt replication for fault tolerance by distributing
replicas of KV pairs across nodes. However, existing distributed KV stores often manage all …

Distributed storage employs replication to mask failures and improve availability. However,
these systems typically exhibit a hard tradeoff between consistency and performance …

When the amount of data is increasing, most of the distributed key-value storage systems
use the quorum based consistent replica selection algorithms for fault-tolerance and load …

High performance distributed storage systems face the challenge of load imbalance caused
by skewed and dynamic workloads. This paper introduces Pegasus, a new storage system …

High performance distributed storage systems face the challenge of load imbalance caused
by skewed and dynamic workloads. This paper introduces Pegasus, a new storage …

Distributed storage systems employ replication to improve performance and reliability. To
provide low latency data access, replicas are often required to accept updates without …

In distributed key-value stores, multiple replica servers are always available for each key-
value access operation when the eventual consistency model is employed. Accordingly, the …

Key-value (KV) stores based on the LSM tree have become a foundational layer in the
storage stack of datacenters and cloud services. Current approaches for achieving reliability …

Distributed storage systems often triplicate data to reduce the risk of permanent data loss,
thereby tolerating at least two simultaneous disk failures at the price of 2/3 of the capacity. To …

Key-value stores (KVS) are finding use in Big Data applications as the store offers a flexible
data model, scalability in number of distributed nodes, and high availability. In a cloud …