7 citations · 19 across the 13 of their papers we have counts for
15 papers
Constrained Federated Reinforcement Learning for Secure Offloading in Vehicular Edge Computing
Zhiyu Wang, Muhammed F. Esgin, Mohammad Goudarzi
Vehicular Edge Computing (VEC) reduces latency for computation-intensive vehicular applications by offloading tasks to roadside edge servers. Real vehicular workloads, however, con…
Performance and Security Aware Distributed Service Placement in Fog Computing
Mohammad Goudarzi, Arash Shaghaghi, Zhiyu Wang +1
The rapid proliferation of IoT applications has intensified the demand for efficient and secure service placement in Fog computing. However, heterogeneous resources, dynamic worklo…
A Knowledge Distillation-empowered Adaptive Federated Reinforcement Learning Framework for Multi-Domain IoT Applications Scheduling
Zhiyu Wang, Mohammad Goudarzi, Mingming Gong +1
The rapid proliferation of Internet of Things (IoT) applications across heterogeneous Cloud-Edge-IoT environments presents significant challenges in distributed scheduling optimiza…
ReinFog: A Deep Reinforcement Learning Empowered Framework for Resource Management in Edge and Cloud Computing Environments
Zhiyu Wang, Mohammad Goudarzi, Rajkumar Buyya
The growing IoT landscape requires effective server deployment strategies to meet demands including real-time processing and energy efficiency. This is complicated by heterogeneous…
TF-DDRL: A Transformer-enhanced Distributed DRL Technique for Scheduling IoT Applications in Edge and Cloud Computing Environments
Zhiyu Wang, Mohammad Goudarzi, Rajkumar Buyya
With the continuous increase of IoT applications, their effective scheduling in edge and cloud computing has become a critical challenge. The inherent dynamism and stochastic chara…
Deep Reinforcement Learning-based Scheduling for Optimizing System Load and Response Time in Edge and Fog Computing Environments
Zhiyu Wang, Mohammad Goudarzi, Mingming Gong +1
Edge/fog computing, as a distributed computing paradigm, satisfies the low-latency requirements of ever-increasing number of IoT applications and has become the mainstream computin…
μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog computing Environments
Mohammad Goudarzi, Maria A. Rodriguez, Majid Sarvi +1
Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet of Things (IoT) use cases, particularly latency-critical applications. Smart devi…
FLight: A Lightweight Federated Learning Framework in Edge and Fog Computing
Wuji Zhu, Mohammad Goudarzi, Rajkumar Buyya
The number of Internet of Things (IoT) applications, especially latency-sensitive ones, have been significantly increased. So, Cloud computing, as one of the main enablers of the I…
Quality of Service (QoS)-driven Edge Computing and Smart Hospitals: A Vision, Architectural Elements, and Future Directions
Rajkumar Buyya, Satish N. Srirama, Redowan Mahmud +3
The Internet of Things (IoT) paradigm is drastically changing our world by making everyday objects an integral part of the Internet. This transformation is increasingly being adopt…
Scheduling IoT Applications in Edge and Fog Computing Environments: A Taxonomy and Future Directions
Mohammad Goudarzi, Marimuthu Palaniswami, Rajkumar Buyya
Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the network with low latency and high-access bandwidth to support a diverse range of IoT applica…
Container Orchestration in Edge and Fog Computing Environments for Real-Time IoT Applications
Zhiyu Wang, Mohammad Goudarzi, Jagannath Aryal +1
Resource management is the principal factor to fully utilize the potential of Edge/Fog computing to execute real-time and critical IoT applications. Although some resource manageme…
A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments
Mohammad Goudarzi, Marimuthu Palaniswami, Rajkumar Buyya
Fog/Edge computing is a novel computing paradigm supporting resource-constrained Internet of Things (IoT) devices by the placement of their tasks on the edge and/or cloud servers.…
IFogSim2: An Extended iFogSim Simulator for Mobility, Clustering, and Microservice Management in Edge and Fog Computing Environments
Redowan Mahmud, Samodha Pallewatta, Mohammad Goudarzi +1
Internet of Things (IoT) has already proven to be the building block for next-generation Cyber-Physical Systems (CPSs). The considerable amount of data generated by the IoT devices…
A Distributed Application Placement and Migration Management Techniques for Edge and Fog Computing Environments
Mohammad Goudarzi, Marimuthu Palaniswami, Rajkumar Buyya
Fog/Edge computing model allows harnessing of resources in the proximity of the Internet of Things (IoT) devices to support various types of real-time IoT applications. However, du…
Resource Management in Edge and Fog Computing using FogBus2 Framework
Mohammad Goudarzi, Qifan Deng, Rajkumar Buyya
Edge/Fog computing is a novel computing paradigm that provides resource-limited Internet of Things (IoT) devices with scalable computing and storage resources. Compared to cloud co…