venue: IC year: 2024 selected: - title: "Revisiting Edge AI: Opportunities and Challenges" authors: - Tobias Meuser - Lauri Lovén - Monowar Bhuyan - Shishir G. Patil - Schahram Dustdar - Atakan Aral - Suzan Bayhan - Christian Becker 0001 - Eyal de Lara - Aaron Yi Ding - Janick Edinger - James Gross - Nitinder Mohan - Andy D. Pimentel - Etienne Rivière - Henning Schulzrinne - Pieter Simoens - Gürkan Solmaz - Michael Welzl tldr: "A multi-author position paper that revisits the state of edge AI, cataloguing deployment barriers and open research problems across hardware, networking, and software layers." why_notable: "Brings together 19 leading researchers to synthesize the field's most pressing edge AI challenges, making it an authoritative reference for practitioners and researchers planning edge deployments." - title: "On Causality in Distributed Continuum Systems" authors: - Víctor Casamayor-Pujol - Boris Sedlak - Praveen Kumar Donta - Schahram Dustdar tldr: "Formalizes causal reasoning across cloud-to-edge continuum systems, providing a conceptual framework for tracking cause-and-effect relationships in highly distributed deployments." why_notable: "Addresses a foundational gap in distributed systems theory that becomes critical when debugging or optimizing multi-tier edge–cloud pipelines." - title: "Beyond Von Neumann in the Computing Continuum: Architectures, Applications, and Future Directions" authors: - Dragi Kimovski - Nishant Saurabh - Matthijs Jansen - Atakan Aral - Auday Al-Dulaimy - André B. Bondi - Antonino Galletta - Alessandro V. Papadopoulos - Alexandru Iosup - Radu Prodan tldr: "Surveys non-von Neumann architectural paradigms—neuromorphic, in-memory, and dataflow computing—and maps them onto continuum computing use cases spanning edge to cloud." why_notable: "Offers a rare cross-cutting view of how emerging hardware architectures reshape the design space for distributed Internet applications." - title: "ARASEC: Adaptive Resource Allocation and Model Training for Serverless Edge-Cloud Computing" authors: - Dewant Katare - Eduard Marin - Nicolas Kourtellis - Marijn Janssen - Aaron Yi Ding tldr: "Proposes ARASEC, a system that jointly optimizes resource allocation and on-device model training for serverless functions deployed across edge and cloud nodes." why_notable: "Demonstrates measurable efficiency gains in a realistic serverless edge-cloud setting, directly informing how operators should provision heterogeneous serverless infrastructure." - title: "WebAssembly at the Edge: Benchmarking a Serverless Platform for Private Edge Cloud Systems" authors: - Giuseppe De Palma - Saverio Giallorenzo - Jacopo Mauro - Matteo Trentin - Gianluigi Zavattaro tldr: "Benchmarks a WebAssembly-based serverless runtime on private edge cloud hardware, measuring cold-start latency, throughput, and isolation overhead compared to container-based alternatives." why_notable: "Provides concrete empirical data that practitioners need when evaluating WebAssembly as a lightweight alternative to Docker for edge serverless deployments." - title: "HeROsim: An Allocation and Scheduling Simulator for Evaluating Serverless Orchestration Policies" authors: - Vincent Lannurien - Laurent d'Orazio - Olivier Barais - Stéphane Paquelet - Jalil Boukhobza tldr: "Introduces HeROsim, an open simulator that models serverless function placement and scheduling policies across heterogeneous infrastructure, enabling fair policy comparison without live cluster costs." why_notable: "Fills a practical tooling gap for researchers and platform engineers who need reproducible evaluation environments for serverless orchestration algorithms." - title: "Hierarchical Network Data Analytics Framework for 6G Network Automation: Design and Implementation" authors: - Youbin Jeon - Sangheon Pack tldr: "Designs and implements a hierarchical analytics framework that aggregates network telemetry at multiple granularities to automate management decisions in 6G deployments." why_notable: "Bridges the gap between 6G vision and practical automation by providing a concrete architecture with implementation details and empirical evaluation." - title: "Digital-Twin-Driven End-to-End Network Slicing Toward 6G" authors: - Mahnoor Yaqoob - Ramona Trestian - Mallik Tatipamula - Huan Xuan Nguyen tldr: "Proposes a digital-twin framework that continuously models and reconfigures end-to-end network slices, enabling dynamic SLA enforcement across heterogeneous 6G infrastructure." why_notable: "Connects digital twin technology to the operational problem of network slice management, a key requirement for 6G service assurance." - title: "The Internet of Things in the Era of Generative AI: Vision and Challenges" authors: - Xin Wang 0120 - Zhongwei Wan - Arvin Hekmati - Mingyu Zong - Samiul Alam - Mi Zhang 0002 - Bhaskar Krishnamachari tldr: "Examines how generative AI models can be integrated into IoT pipelines for data synthesis, anomaly detection, and on-device inference, and identifies the key resource and privacy constraints." why_notable: "Provides a structured research agenda for one of the most active intersections in Internet computing, relevant to both IoT platform designers and ML practitioners." - title: "Distributed Federated Deep Learning in Clustered Internet of Things Wireless Networks With Data Similarity-Based Client Participation" authors: - Evangelia Fragkou 0001 - Eleftheria Chini - Maria Papadopoulou 0008 - Dimitrios K. Papakostas - Dimitrios Katsaros 0001 - Schahram Dustdar tldr: "Proposes a clustered federated learning scheme for wireless IoT networks that selects participating clients based on data similarity, reducing communication overhead and improving model convergence." why_notable: "Addresses a core practical challenge in IoT federated learning—heterogeneous and non-IID data—with an empirically validated participation strategy."