Datacenter operations today provide a plethora of new queueing and scheduling problems.
The notion of a “job” has become more general and multi-dimensional. The ways in which …

Multiserver-job systems, where jobs require concurrent service at many servers, occur
widely in practice. Essentially all of the theoretical work on multiserver-job systems focuses …

We consider the problem of scheduling to minimize mean response time in M/G/1 queues
where only estimated job sizes (processing times) are known to the scheduler, where a job …

Queueing delays are ubiquitous in many domains, including computer systems, service
systems, communication networks, supply chains, and transportation. Queueing and …

In this study, we investigate a real-time system where computationally intensive tasks are
executed using cloud computing platforms in data centers. These data centers are designed …

Dispatching systems, where arriving jobs are immediately assigned to one of multiple
queues, are ubiquitous in computer systems and service systems. A natural and practically …

The Gittins policy is a highly general scheduling policy that minimizes a wide variety of mean
holding cost metrics in the M/G/1 queue. Perhaps most famously, Gittins minimizes mean …

We consider the classic problem of preemptively scheduling jobs of unknown size (aka
service time) in a queue to minimize mean number-in-system, or equivalently mean …

We consider scheduling in the M/G/1 queue with unknown job sizes. It is known that the
Gittins policy minimizes mean response time in this setting. However, the behavior of the tail …

Bayesian optimization is a technique for efficiently optimizing unknown functions in a black-
box manner. To handle practical settings where gathering data requires use of finite …