With the wide adoption of large-scale internet services and big data, the cloud has become
the ideal environment to satisfy the ever-growing storage demand. In this context, data …

Modern storage stacks increasingly aim to intellegently optimize data accesses to improve
latency, throughput, and energy consumption. Additionally, new storage setups become …

In the era of big data, log-structured merge-tree (LSM-tree) based key–value stores (KV
stores) have become an effective alternative to the traditional relational database owing to …

With the wide adoption of large-scale Internet services and big data, the cloud has become
the ideal environment to satisfy the ever-growing storage demand, thanks to its seemingly …

In large scale storage systems such as data centers, data layouts need to be reconfigured
over time for load balancing or in the event of system failure/upgrades. The data-migration …

In this paper, we consider the problem of data migration in large scale storage systems,
where a massive set of data needs to be transferred within a set of disks. The objective is to …

Live data migration is an important technique for key-value stores. However, due to the
stateful feature, new virtualization technology, stringent low latency requirements and …

Data placement considerably affects the I/O performance of distributed storage systems such
as HDFS. An ideal placement algorithm should keep the I/O load evenly distributed among …

In large scale storage systems such as data centers, the layout of data on storage disks
needs to be frequently reconfigured for load balancing purposes or in the event of system …

Load balance and power proportionality are both important aspects in constructing high-
performance and cost-effective distributed storage systems. However, traditional replica …