Google's Borg system is a cluster manager that runs hundreds of thousands of jobs, from
many thousands of different applications, across a number of clusters each with up to tens of …

The growing heterogeneity due to diverse Cloud workloads such as Big Data, IoT and
Business Data analytics, requires precise characterization to design a successful capacity …

To improve resource efficiency and design intelligent scheduler for clouds, it is necessary to
understand the workload characteristics and machine utilization in large-scale cloud data …

In data centers, packet losses cause high retransmission delays, which is harmful to many
real-time workloads. To prevent packet losses, the lossless fabrics have been deployed in …

Server workload in the form of cloud-end clusters is a key factor in server maintenance and
task scheduling. How to balance and optimize hardware resources and computation …

With increased demand for computing resources at a lower cost by end-users, cloud
infrastructure providers need to find ways to protect their revenue. To achieve this …

Cloud computing with large-scale datacenters provides great convenience and cost-
efficiency for end users. However, the resource utilization of cloud datacenters is very low …

In this paper, we analyze a workload trace from the Google cloud cluster and characterize
the observed failures. The goal of our work is to improve the understanding of failures in …

Improving energy efficiency and lowering operational costs are the main challenges faced in
systems with multiple servers. One prevalent objective in such systems is to minimize the …

Cloud computing has gained interest amongst commercial organizations, research
communities, developers and other individuals during the past few years. In order to move …