As mobile computing has been developed for decades, a new model for mobile computing,
namely, mobile cloud computing, emerges resulting from the marriage of powerful yet …

Increasing scale and the need for rapid response to changing requirements are hard to meet
with current monolithic cluster scheduler architectures. This restricts the rate at which new …

Small jobs, that are typically run for interactive data analyses in datacenters, continue to be
plagued by disproportionately long-running tasks called stragglers. In the production …

Enterprises are moving their business-critical workloads to public clouds at an accelerating
pace. Multi-tenancy is a crucial tenet for cloud data service providers allowing them to …

The continuous shift towards data-driven approaches to business, and a growing attention to
improving return on investments (ROI) for cluster infrastructures is generating new …

Large-scale public cloud providers invest billions of dollars into their cloud infrastructure and
operate hundreds of thousands of servers across the globe. For various reasons, much of …

Predictive cloud resource management has been widely adopted to overcome the
limitations of reactive cloud autoscaling. The predictive resource management is highly …

We introduce ChronoStream, a distributed system specifically designed for elastic stateful
stream computation in the cloud. ChronoStream treats internal state as a first-class citizen …

In this paper, we present Sailfish, a new Map-Reduce framework for large scale data
processing. The Sailfish design is centered around aggregating intermediate data …

We argue for breaking data-parallel jobs in compute clusters into tiny tasks that each
complete in hundreds of milliseconds. Tiny tasks avoid the need for complex skew mitigation …