Supporters
This workshop is supported by:
The Cloud-Edge Continuum is a new hyper-distributed computing paradigm that aims at seamlessly interconnecting and abstracting the computing power and storage capacity of the Cloud with the data processing capabilities of edge devices, IoT devices, and sensors. Intelligently balancing tasks in a continuum enables faster response times, lower latency, and more efficient use of network bandwidth. However, efficiently managing extremely heterogeneous Cloud and Edge resources is a pressing concern in real-world large-scale implementations. Such heterogeneity refers to differences in network capabilities, processing power, software stack, APIs, and security protocols across the Cloud-Edge Continuum infrastructure. This raises significant challenges for the network community to develop new and efficient protocols and communication services. Given the potential benefits of the Cloud-Edge Continuum, it is important to explore the current state-of-the-art research and identify the challenges and opportunities in this area.
The Cloud-Edge Continuum (CEC) workshop aims to bring together researchers and practitioners from academia and industry to discuss the latest research, trends, and challenges in ecosystems and environments based on Cloud-Edge Continuum paradigm. The primary goal of this workshop is to foster collaboration and exchange of ideas among researchers and stakeholders. The workshop can provide a platform for participants to share their experiences, best practices, case studies, and to identify emerging research areas and potential solutions to existing challenges. By bringing together experts from different domains, the CEC workshop also aims to provide insights into how Cloud-Edge Continuum can be applied in various fields, such as healthcare, transportation, smart cities, and manufacturing.
We welcome submissions of original research, work-in-progress, and proof of concepts describing original ideas and presenting new directions. We invite submissions covering the aspects around the design, development, and evaluation of architectures, technologies, and applications for the Cloud-Edge Continuum, including but not limited to:
July 10, 2026 June 26, 2026
July 10, 2026 July 03, 2026
August 11, 2026
August 25, 2026
Submissions must be original, unpublished work, and not under consideration at another conference or journal. Paper submissions should adhere to the IEEE Conference formatting requirements with double column and the font size must be 10 points. The length of the final paper with all its content (including references) must not exceed 6 pages. Papers must include author’s names and affiliations for single-blind peer reviewing by the PC. Authors of accepted papers are expected to present their papers at the workshop. The IEEE template available here.
Please submit your paper using CEC'26 workshop's HotCRP link.
Tomas Cerny earned his PhD from the Czech Technical University in Prague. He has held professorships in Prague and at Baylor University and is currently a faculty member at the University of Arizona at the School of Electrical, Computing and Software Engineering. His research focuses on cloud-native system evolution, software architecture, technical debt, and static analysis. For 19 years, he served as the Global Infrastructure Director of the International Collegiate Programming Contest (ICPC), and he is a UPE council member. He has authored more than 200 publications, primarily in cloud-native systems and code analysis. His contributions to research, education, and service have been recognized with numerous awards, including the 2026 PhD Mentorship Award from the University of Arizona, the 2025 FindAPhD.com PhD Supervisor Award, the 2023 Baylor Scholarship Award, the ACM SIGAPP Outstanding Service Awards in 2018 and 2015, and the 2011 ICPC Joseph S. DeBlasi Outstanding Contribution Award. He is actively engaged in the scientific community. He has served on the organizing committees of major international conferences and workshops, including IEEE SOSE, ESOCC, SANER, ACM SAC, ACM RACS, and ISD.
Dr. Nariman Mani is Chief Technology Officer and Director of Research and Development at NutroSal Inc. His research focuses on dependable AI-enabled software, cloud-native and microservice architectures, software assurance, and privacy-preserving orchestration. He brings more than 18 years of experience spanning software engineering, systems architecture, quality assurance, and technology leadership. His professional background combines hands-on engineering with the design and validation of dependable software systems. His technical work spans cloud-native architectures, software testing, performance engineering, applied AI, and privacy-preserving digital platforms. He brings an industrial perspective to how organizations introduce AI-enabled capabilities while maintaining visibility into system behavior and control over operational risk. Dr. Mani holds a PhD in Systems and Computer Engineering from Carleton University and is a Professional Engineer in Ontario, Canada. Alongside his industry work, he contributes to research at the University of Arizona, connecting practical engineering challenges with research in software architecture and dependable AI-enabled systems.
Session Chair: Dr. Ahmed Khalid
Speaker: Dr. Tomas Cerny (University of Arizona)
Title: Cloud-Native Change Impact Analysis: Understanding What Will Break Before It Breaks
Abstract: Cloud-native systems enable unprecedented speed of software evolution, but their distributed and continuously changing nature makes it increasingly difficult to understand the consequences of change. This keynote explores change impact analysis for cloud-native systems, combining software architecture, static analysis, dependency analysis, and repository mining to identify how changes propagate across services, APIs, data, and infrastructure. It explores how AI can enable more intelligent and trustworthy impact analysis. The talk will highlight a fundamental challenge for modern software engineering: how can we change cloud-native systems rapidly while understanding what those changes may break?
Session Chair: Dr. Ahmed Khalid
1100–1120
Title: Orchestrating Large Language Models Deployment Near the Edge
Authors: Ahmed Salah Tawfik Ibrahim, Rana Abu Bakar, Francesco Paolucci & Filippo Cugini (CNIT); Ashley Degl’Innocenti & Emilio Paolini (Scuola Superiore Sant’Anna)
Duration: 20 min
1120–1140
Title: SENTRY: Drift-Aware Validation Placement for AI Services in the Cloud-Edge Continuum
Authors: Nariman Mani, Shakthi Weerasinghe & Tomas Cerny (University of Arizona); Xiaozhou Li (Xi’an Jiaotong-Liverpool University)
Duration: 20 min
1140–1200
Title: A Reward-Guided Agentic Architecture for Metadata Generation in the Cloud–Edge Continuum
Authors: Hassan Mehmood, Muhammad Ramish, Ekaterina Gilman, Lauri Lovén & Mohammad Atta Ullah (University of Oulu); Ahmed Khalid (Dell Technologies)
Duration: 20 min
1200–1220
Title: A Cloud-Edge Continuum Architecture for Real-Time Hyperspectral Inspection in Smart Manufacturing
Authors: Muhammad Huzaifa Javaid, Muhammad Ramish, Dinesh Sah, Lauri Lovén, Hassan Mehmood, Hamza Irfan, Timo Rahkonen & Pekka Huttunen (University of Oulu)
Duration: 20 min
1220–1230 — Discussion & Q&A
Session Chair: Dr. Ahmed Khalid
Speaker: Dr. Nariman Mani, CTO and Director of R&D, NutroSal Inc.
Title: AI in Production: Engineering Secure and Resilient Systems Across the Cloud–Edge Continuum
Abstract: Deploying AI across devices, edge gateways, and cloud services raises a practical question: how do we keep systems useful, secure, and accountable when connectivity is intermittent and components fail? From an industrial perspective, production readiness requires explicit decisions about data handling, failure detection, and recovery. This industrial keynote examines the engineering decisions behind operating AI-enabled systems across the cloud–edge continuum, including which responsibilities should remain local, which require cloud coordination, and which actions should be restricted when the system cannot verify its data, permissions, or operating conditions. The central question is: how can we distribute intelligence without losing the ability to detect failure and restore service?
Session Chair: Dr. Hassan Mehmood
1530–1550
Title: Privacy-Preserving Network Telemetry with FHE: A Comparative Evaluation on DPU and GPU Platforms
Authors: Matteo Sandrucci, Ashley Degl’Innocenti, Marco Lucio Mangiacapre & Piero Castoldi (Scuola Superiore Sant’Anna); Stefano Marri Malacrida & Benedetta Picano (Università degli Studi di Firenze); Filippo Cugini (CNIT); Juan Jose Vegas Olmos (NVIDIA)
Duration: 20 min
1550–1610
Title: Production Trace From a Public CDN for Caching and Content-Placement Research
Authors: Mario Perez-Jimenez (Ericsson Research); Cláudia Marinho, Mafalda Santos & Alexandre Ulisses (EVS Broadcast Equipment); Tarek Zaarour & Ahmed Khalid (Dell Technologies)
Duration: 20 min
1610–1630
Title: Multi-Hop Post-Quantum Chain-of-Custody for Automotive Telemetry in the Cloud–Edge Continuum
Authors: Mihail Gaianu & Petre-Alexandru Dumitru (West University of Timișoara)
Duration: 20 min
1630–1650
Title: Latency-Aware Inference Routing for Resilient Multimodal AI Across the Cloud-Edge Continuum
Authors: Sean Ahearne, Denis Solodovnikov & Anthony Jreij (Dell Technologies)
Duration: 20 min
1650–1700 — Discussion & Q&A
For any question or doubt, please reach us at Ahmed.Khalid@dell.com and Raul.Gracia@dell.com.
This workshop is supported by: