Mobile users typically have high demand on localized and location-based information
services. To always retrieve the localized data from the remote cloud, however, tends to be …

Abstract Throughout its history, Operational Research has evolved to include methods,
models and algorithms that have been applied to a wide range of contexts. This …

Resource allocation and scheduling strategies for deep learning training (DLT) jobs have a
critical impact on their average job completion time (JCT). Unfortunately, traditional …

In many traditional job scheduling settings, it is assumed that one knows the time it will take
for a job to complete service. In such cases, strategies such as shortest job first can be used …

Many diverse healthcare systems, including hospitals, laboratories, pharmaceutical
business, radiology, organ transplant etc. have been modelled and studied using queuing …

Operations Research: A Practical Introduction is just that: a hands-on approach to the field of
operations research (OR) and a useful guide for using OR techniques in scientific decision …

Quality-of-service and SLA guarantees are among the major challenges of cloud-based
services. In this paper we first present a new cloud model called SLAaaS—SLA aware …

Electrification of transportation is considered as one of the most promising ways to mitigate
climate change and reduce national security risks from oil and gasoline imports. Fast …

Abstract The Industrial Internet of Things (IIoTs) is an emerging area that forms the
collaborative environment for devices to share resources. In IIoT, many sensors, actuators …

Queueing models are important tools for the design and management of emergency
departments (EDs). In this survey, we examine the contributions of queueing theory (QT) in …