260 citations · 582 across the 29 of their papers we have counts for
7 papers · 1 filter
REACH: Reinforcement Learning for Adaptive Microservice Rescheduling in the Cloud-Edge Continuum
Xu Bai, Muhammed Tawfiqul Islam, Rajkumar Buyya +1
Cloud computing, despite its advantages in scalability, may not always fully satisfy the low-latency demands of emerging latency-sensitive pervasive applications. The cloud-edge co…
Resilience Evaluation of Kubernetes in Cloud-Edge Environments via Failure Injection
Zihao Chen, Mohammad Goudarzi, Adel Nadjaran Toosi
Kubernetes has emerged as an essential platform for deploying containerised applications across cloud and edge infrastructures. As Kubernetes gains increasing adoption for mission-…
Efficient Routing of Inference Requests across LLM Instances in Cloud-Edge Computing
Shibo Yu, Mohammad Goudarzi, Adel Nadjaran Toosi
The rising demand for Large Language Model (LLM) inference services has intensified pressure on computational resources, resulting in latency and cost challenges. This paper introd…
A Multi-Armed Bandit-Based Participant Selection Method for Federated Recommendation Systems
Jintao Liu, Mohammad Goudarzi, Adel Nadjaran Toosi
Federated Recommendation Systems (FRS) enable privacy-preserving model training by keeping user data on edge devices. However, the practical deployment of FRS in Edge-Cloud environ…
ECORE: Energy-Conscious Optimized Routing for Deep Learning Models at the Edge
Daghash K. Alqahtani, Maria A. Rodriguez, Muhammad Aamir Cheema +2
Edge computing enables data processing closer to the source, significantly reducing latency, an essential requirement for real-time vision-based analytics such as object detection…
Smart Ride and Delivery Services with Electric Vehicles: Leveraging Bidirectional Charging for Profit Optimisation
Jinchun Du, Bojie Shen, Muhammad Aamir Cheema +1
With the rising popularity of electric vehicles (EVs), modern service systems, such as ride-hailing delivery services, are increasingly integrating EVs into their operations. Unlik…
Personalizing Federated Learning for Hierarchical Edge Networks with Non-IID Data
Seunghyun Lee, Omid Tavallaie, Shuaijun Chen +4
Accommodating edge networks between IoT devices and the cloud server in Hierarchical Federated Learning (HFL) enhances communication efficiency without compromising data privacy. H…