Abstract Multiserver-job (MSJ) systems, where jobs need to run concurrently across many
servers, are increasingly common in practice. The default service ordering in many settings …

Multiserver jobs, which are jobs that occupy multiple servers simultaneously during service,
are prevalent in today's computing clusters. But little is known about the delay performance …

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 …

Modern data centers feature an extensive array of cores that handle quite a diverse range of
jobs. Recent traces, shared by leading cloud data center enterprises like Google and …

We consider a multiserver queue where jobs request for a varying number of servers for a
random service time. The requested number of servers is assigned to each job following a …

We consider the optimal scheduling problem in the M/G/1 queue. While this is a thoroughly
studied problem when the target is to minimize the mean delay, there are still open …

In this paper, we study systems where each job or request can be split into a flexible number
of sub-jobs up to a maximum limit. The number of sub-jobs a job is split into depends on the …

Scheduling theory is a key tool for reducing latency (ie response time) in queueing systems.
Scheduling, ie choosing the order in which to serve jobs, can reduce response time by an …

Ever since the advent of" multiserver jobs"(jobs that require more than one server or core
simultaneously), practitioners have been faced with the question of how to pack these jobs …

We study the problem of scheduling jobs in a queueing system, specifically an M/G/1 with
light-tailed job sizes, to asymptotically optimize the response time tail. This means …