5 papers
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…
GraphFlash: Enabling Fast and Elastic Graph Processing on Serverless Infrastructure
Chen Zhao, Parsa Poorsistani, Mohammad Goudarzi +2
Graph processing systems are essential for analyzing large-scale data with complex relationships, yet most existing frameworks rely on statically provisioned clusters, resulting in…
LLM-Driven Intent-Based Privacy-Aware Orchestration Across the Cloud-Edge Continuum
Zijie Su, Muhammed Tawfiqul Islam, Mohammad Goudarzi +1
With the rapid advancement of large language models (LLMs), efficiently serving LLM inference under limited GPU resources has become a critical challenge. Recently, an increasing n…
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…
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-…