Dynamic Flexible Job Shop Scheduling (DFJSS) is a critical combinatorial optimisation
problem known for its dynamic nature and flexibility of machines. Traditional scheduling …

Dynamic workflow scheduling (DWS) is a challenging and important optimization problem in
cloud computing, aiming to execute multiple heterogeneous workflows on dynamically …

Cloud computing has emerged as a promising platform for running scientific workflows
across various domains. Scientists can take advantage of different cloud service models …

Software-defined networking (SDN) allows flexible and centralized control in cloud data
centers. An elastic set of distributed SDN controllers is often required to provide sufficient yet …

The advent of distributed computing and mobile clouds made it possible to transfer and
distribute the heavy processes of complex workflows to the cloud. Managing and with the …

Abstract Genetic Programming Hyper-heuristics (GPHH) have been successfully used to
evolve scheduling rules for Dynamic Workflow Scheduling (DWS) as well as other …

As a key cloud management problem, Cost-aware Dynamic Multi-Workflow Scheduling
(CDMWS) aims to assign virtual machine (VM) instances to execute tasks in workflows so as …

Dynamic flexible job shop scheduling (DFJSS) has attracted a lot of attention from both
academics and industries because of its widespread industrial impact in the real world. The …

Abstract Deep Reinforcement Learning (Deep RL) is increasingly used to cope with the
open-world assumption in service-oriented systems. Deep RL was successfully applied to …

Intelligent applications heavily rely on deep neural network (DNN) inference services
executed on edge devices to fulfill functional prerequisites while safeguarding user data …