With the rapid development of cloud systems, an increasing number of service workloads
are deployed in the private cloud and/or public cloud. Although large cloud providers such …

Constrained cooperative multi-agent reinforcement learning (MARL) is an emerging
learning framework that has been widely applied to manage multi-agent systems, and many …

We address the real problem of safe, robust, adaptive resource oversubscription in uncertain
environments with our proposed novel technique of chance-constrained imitation learning …

Cloud platforms remain underutilized despite multiple proposals to improve their utilization
(eg, disaggregation, harvesting, and oversubscription). Our characterization of the resource …

We address the problem of under-utilization of resources in datacenters during cloud
operations, specifically focusing on the challenge of online virtual machine (VM) scheduling …

With the escalating demand for cloud computing services, data centers (DCs) encounter
formidable challenges extending beyond capital investment needs to accommodate …

We address the challenge of learning safe and robust decision policies in presence of
uncertainty in context of the real scientific problem of adaptive resource oversubscription to …

By migrating its workload to larger Data Centers (DCs), the digital realm has been able to
improve its energy efficiency. The consumption due to the increase in usage has thus been …