1.2k citations · 3.6k across the 100 of their papers we have counts for
112 papers
The Geometry of Randomized Smoothing on Feasible Sets
Syed Izhan Khilji, Alireza Furutanpey, Schahram Dustdar
Randomized smoothing certifies the probability of a fixed output event as the center of Gaussian noise moves. Feasibility or confidence filtering reports label probabilities only a…
ARGOS: Reinforcement Learning-Driven Multidimensional Elasticity for Service Orchestration in the Computing Continuum
Javier Mateos-Bravo, Sergio Laso, Juan Luis Herrera +3
Data-intensive services in the Computing Continuum must balance analytics quality, resource usage, and cost across heterogeneous nodes with limited and uneven capacity. This balanc…
Cloud, Edge, or Split? Profiling Onboard and Split Vision-Language Model Deployment for Drone AI
Zoha Azimi, Reza Farahani, Schahram Dustdar +1
Vision-Language Models (VLMs) enable edge devices like unmanned aerial vehicles (UAVs) to interpret visual observations and reason about complex environments using natural-language…
A Kubernetes-Native Request Router for Quality-Aware Inference Serving in the Computing Continuum
Ignjat Karanovic, Pantelis A. Frangoudis, Ivan Čilić +2
We introduce Adaptive Score-based Routing Balancer (ASRB), a dynamic, score-based request routing mechanism for Kubernetes-based service deployments over the computing continuum. A…
FANS: Federated Adaptive Network Search Learning for Heterogeneous Devices
Jiaxin Zhang, Xingwei Wang, Bo Yi +6
Heterogeneous Federated Learning (HFL) aims to train models across devices with diverse resource budgets while preserving data privacy. Existing HFL methods typically bind training…
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…
LipCache: A Local Inference Proxy with Certified Caching for Edge Image Classification Service
Zhengzhe Xiang, Yinlin Chen, Fuli Ying +3
As edge-side vision services continue to expand toward low-latency, high-throughput scenarios, reducing the inference cost of vision models without sacrificing reliability has beco…
LYRA: Label-Free Structural Synchronization and Resource Allocation for UAV Edge Networks
Feng He, Alireza Furutanpey, Paolo Bellavista +4
While deploying hierarchical vision models to process mission-critical tasks, UAV edge systems must adaptively update the models to sustain inference reliability under low-level en…
Clear-Weighted Bit Allocation for Satellite Downlinks
Alireza Furutanpey, Qiyang Zhang, Yujie Huang +2
Earth-observation satellites capture more imagery than intermittent ground contacts can transmit. Onboard systems threshold a cloud detector, discard frames or tiles, and compress…
A Taxonomy of Performance Metrics for the Distributed Computing Continuum
Praveen Kumar Donta, Boris Sedlak, Alfreds Lapkovskis +6
Performance evaluation is essential for understanding, comparing, and improving computing systems, including Distributed Computing Continuum Systems (DCCS). In recent years, comput…
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…
Principled Direction-Free Intrinsic Motivation through Model-Free Epistemic Free-Energy Estimators
Alireza Furutanpey, Schahram Dustdar
Across environments with mixed sources of uncertainty, unsupervised reinforcement learning requires intrinsic motivation that does not precommit to a particular direction of surpri…
Agentic Service-Oriented Computing: A Manifesto for the Next Frontier of Service-Oriented Computing
Amin Beheshti, Rong N. Chang, Boualem Benatallah +7
The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and to…
Incentives and Evidence in Learned Service Orchestration
Syed Izhan Khilji, Alireza Furutanpey, Schahram Dustdar
Reinforcement learning for service orchestration has been the subject of sustained research for over a decade, yet it is not used in production at scale. The usual explanation is t…
Fair Comparison of Scheduling Algorithms on Heterogeneous Edge Clusters: A Continuous Adaptive Benchmark
Zihang Wang, Boris Sedlak, Juan Luis Herrera +1
Modern Artificial Intelligence (AI) workloads deployed across the heterogeneous tiers of an edge--cloud continuum must satisfy multi-dimensional Service Level Objectives (SLOs) ove…
Orchestrating Serverless Applications in the Edge Cloud Space Continuum: What Breaks and What is Next?
Hadi Tabatabaee Malazi, Reza Farahani, Nitinder Mohan +1
Serverless computing has matured into an effective execution model for edge cloud environments, enabling function level decomposition, demand driven scaling, and workflow execution…
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…
Credibility Trilemma in Polymatroidal Service Markets
Lauri Lovén, Sujit Gujar, Kalle Timperi +4
Mechanism-mediated service markets with polymatroidal feasibility admit efficient, dominant-strategy incentive-compatible (DSIC) allocation, but these guarantees implicitly assume…
Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safety
Muhammad Bilal, Jon Crowcroft, Ruizhi Wang +2
Large language models (LLMs) are increasingly being used in network operations (NetOps) and artificial intelligence for IT operations (AIOps) for tasks ranging from telemetry retri…
Active Inference-Based Adaptive Routing for Heterogeneous Edge AI Services
Zihang Wang, Boris Sedlak, Schahram Dustdar
Edge computing enables AI inference closer to data sources, reducing latency and bandwidth costs. However, orchestrating AI services across the cloud-edge continuum remains challen…
Pricing-Driven Resource Allocation in the Computing Continuum
Alejandro García-Fernández, Boris Sedlak, José Antonio Parejo +3
Deploying applications across the computing continuum requires selecting infrastructure nodes from geographically distributed and heterogeneous environments while satisfying constr…
DQ-Ladder: A Deep Reinforcement Learning-based Bitrate Ladder for Adaptive Video Streaming
Reza Farahani, Zoha Azimi, Vignesh V Menon +4
Adaptive streaming of segmented video over HTTP typically relies on a predefined set of bitrate-resolution pairs, known as a bitrate ladder. However, fixed ladders often overlook v…
Agentic Service Markets Across the Computing Continuum: A Polymatroidal Architecture
Lauri Lovén, Alaa Saleh, Reza Farahani +5
Autonomous AI agents are becoming economic actors. They compose deadline-bound services across the device-edge-cloud continuum and contend for capacity no single operator owns. Thi…
Visual Insights into Agentic Optimization of Pervasive Stream Processing Services
Boris Sedlak, Víctor Casamayor Pujol, Schahram Dustdar
Processing sensory data close to the data source, often involving Edge devices, promises low latency for pervasive applications, like smart cities. This commonly involves a multitu…