5 papers
DRLM: Deep Reinforcement Learning-Based LLM Query Orchestration in Edge Environments
Reza Farahani, Zoha Azimi Ourimi, Mario Colosi +3
Large language model (LLM) services increasingly process heterogeneous queries with diverse latency, accuracy, and resource requirements. While edge deployment reduces response tim…
LMEdge: QoS-Aware LLM Inference Orchestration on Edge Clusters
Reza Farahani, Zoha Azimi, Mario Colosi +1
Large language model (LLM) services increasingly operate on edge infrastructure, enabling low-latency and privacy-preserving AI services. However, efficiently serving LLM requests…
ClusterLess: Deadline-Aware Serverless Workflow Orchestration on Federated Edge Clusters
Reza Farahani, Mario Colosi, Ilir Murturi +4
The recent convergence of edge computing, serverless execution, and Kubernetes (K8s) based container orchestration has enabled the processing of application workflows close to data…
Osmotic Learning: A Self-Supervised Paradigm for Decentralized Contextual Data Representation
Mario Colosi, Reza Farahani, Maria Fazio +2
Data within a specific context gains deeper significance beyond its isolated interpretation. In distributed systems, interdependent data sources reveal hidden relationships and lat…
Serverless Everywhere: A Comparative Analysis of WebAssembly Workflows Across Browser, Edge, and Cloud
Mario Colosi, Reza Farahani, Lauri Loven +2
WebAssembly (Wasm) is a binary instruction format that enables portable, sandboxed, and near-native execution across heterogeneous platforms, making it well-suited for serverless w…