Scalable and flexible communication networks increasingly conduct the packet processing
for Network Functions (NFs) in General Purpose Computing (GPC) platforms. The …

Existing centralized cloud-based solution is challenging to cope with the explosive growth of
data generated from massive IoT devices to meet the requirements of critical services …

Many resource management problems require sequential decision-making under
uncertainty, where the only uncertainty affecting the decision outcomes are exogenous …

Load balancing in the cloud is a strategy that assures that the overall performance of large-
scale computing systems can be improved by ensuring a uniform allocation of local …

We investigate the control system's computational task scheduling problem within limited
time and with limited CPU cores in the cloud server. We employ a neural network model to …

The efficiency and profitability of cloud data centers are significantly influenced by virtual
machine (VM) placement. However, the Non-Uniform Memory Access (NUMA), which has …

Introduction The migration of business and scientific operations to the cloud and the surge in
data from IoT devices have intensified the complexity of cloud resource scheduling …

A great deal of multi agent reinforcement learning (MARL) work has investigated how
multiple agents effectively accomplish cooperative tasks utilizing value function …

The virtual machine (VM) scheduling problem in cloud brokers that support cloud bursting is
fraught with uncertainty due to the on-demand nature of Infrastructure as a Service (IaaS) …

Deep learning (DL) has become a dominating type of workloads on AI computing platforms.
The performance of such platforms highly depends on how distributed DL jobs are …