Resource management challenges frequently manifest in systems and networks as tough
online decision tasks, for which the proper solution is dependent on an understanding of the …

With the development of the Industrial Internet of Things (IoT), the work of large-scale data
collection makes spatiotemporal crowdsensing (SC) play an important role. Mobile devices …

In cloud computing, how to reasonably allocate computing resources for batch jobs to
ensure the load balance of dynamic clusters and meet user requests is an important and …

Large Language Model (LLM) workloads have distinct prefill and decode phases with
different compute and memory requirements which should ideally be accounted for when …

We consider the problem of efficiently routing jobs that arrive into a central queue to a
system of heterogeneous servers. Unlike homogeneous systems, a threshold policy, that …

The widespread application of AIGC services has driven demand for efficient computational
resources, making effective task scheduling and computation offloading in edge computing …

Congestion at signalized intersections can be alleviated by improving traffic signal control
system's performance. In this context, Deep Reinforcement Learning (DRL) methods are …

In a heterogeneous workflow environment, the uncertainty of task execution times, dynamic
resource changes, and task dependencies' evolution pose significant scheduling …