Kinesis is a novel data placement model for distributed storage systems. It exemplifies three
design principles: structure (division of servers into a few failure-isolated segments) …

Elastic distributed storage systems have been increasingly studied in recent years because
power consumption has become a major problem in data centers. Much progress has been …

Distributed key-value storage systems are widely used in corporations and across the
Internet. Our research seeks to greatly expand the application space for key-value storage …

In the last couple of years a dramatic growth of enterprise data storage capacity can be
observed. As a result, new strategies have been sought that allow servers and storage being …

The ever-growing amount of data requires highly scalable storage solutions. The most
flexible approach is to use storage pools that can be expanded and scaled down by adding …

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 …

With data volumes increasing at a high rate and the emergence of highly scalable
infrastructures (cloud computing, petascale computing), distributed management of data …

With the advent of big data, the I/O subsystems of large-scale compute clusters are
becoming a center of focus. More applications are putting greater demands on end-to-end …

Over the last decade, there has been a tremendous growth in data-intensive applications
and services in the cloud. Data is created on a variety of edge sources such as devices, and …

Emerging large-scale distributed storage systems are faced with the task of distributing
petabytes of data among tens or hundreds of thousands of storage devices. Such systems …