Distributed storage systems are used widely in clouds, databases, and file systems. These
systems store a large amount of data across multiple servers. When a request to access data …

Cloud storage systems frequently have a large user base that requires huge cloud
resources. Sometimes, cloud devices become overloaded because of an imbalance in …

Distributed key-value stores today require frequent key-value shard migration between
nodes to react to dynamic workload changes for load balancing, data locality, and service …

New memory technologies are blurring the previously distinctive performance characteristics
of adjacent layers in the memory hierarchy. No longer are such layers orders of magnitude …

The increasing use of Internet of Things devices coincides with more communication and
data movement in networks, which can exceed existing network capabilities. These devices …

Deciding where to handle services and tasks, as well as provisioning an adequate amount
of computing resources for this handling, is a main challenge of edge computing systems …

Low-latency data service is an increasingly critical challenge for data center applications. In
modern distributed storage systems, proper data placement helps reduce the data …

Key-value stores hold the unprecedented bulk of the data produced by applications such as
social networks. Their scalability and availability requirements often outweigh sacrificing …

Low-latency data access is an important challenge for data center networks. Proper
placement of the data items can reduce the data travel time in the distributed storage …

Recently, many in-memory key-value stores have started using a High-Performance network
protocol, Remote Direct Memory Access (RDMA), to provision ultra-low latency access …