As cloud services grow to span more and more globally distributed datacenters, there is an
increasingly urgent need for automated mechanisms to place application data across these …

We consider a system of compute and storage resources geographically distributed over a
large number of locations connected via a wide-area network. By distributing the resources …

As it has become the norm for cloud providers to host multiple datacenters around the globe,
significant demands exist for inter-datacenter data transfers in large volumes, eg, migration …

As the devices that make up the Internet become more powerful, algorithms that orchestrate
cloud systems are on the verge of putting more responsibility for computation and storage on …

Low latency analytics on geographically distributed datasets (across datacenters, edge
clusters) is an upcoming and increasingly important challenge. The dominant approach of …

Many cloud services are running on geographically distributed datacenters for better
reliability and performance. We consider the emerging problem of joint request mapping and …

Data centre applications for batch processing (eg map/reduce frameworks) and online
services (eg search engines) scale by distributing data and computation across many …

Recent work has made the case for geo-distributed analytics, where data collected and
stored at multiple datacenters and edge sites world-wide is analyzed in situ to drive …

With growing data volumes generated and stored across geo-distributed datacenters, it is
becoming increasingly inefficient to aggregate all data required for computation at a single …

Today's data centers need efficient traffic management to improve resource utilization in
their networks. In this work, we study a joint tenant (eg, server or virtual machine) placement …