| 2025 | 18th IEEE International Conference on Cloud Computing, CLOUD 2025, Helsinki, Finland, July 7-12, 2025 Rong N. Chang, Carl K. Chang, Jingwei Yang, Nimanthi Atukorala, Dan Chen, Sumi Helal, Sasu Tarkoma, Qiang He, Tevfik Kosar, Claudio A. Ardagna, Feras Awaysheh, Volker Hilt, Yogesh Simmhan |
| 2025 | Accelerating RL-Based Scheduler Adaptation with Transfer Learning in Evolving HPC Architectures. Lingfei Wang, Maria A. Rodriguez, Nir Lipovetzky |
| 2025 | An Experimental Validation of Architectural Measures for Cloud-Native Quality Evaluations. Robin Lichtenthäler, Guido Wirtz |
| 2025 | Automated LLM Deployment and Evaluation: A Cloud-Native Approach Using LLM-as-a-Judge. Ansar Rafique, Brian D. Marsden |
| 2025 | Avoiding Pitfalls in Networked Key-Value Store for Tiered Memory. Seungmin Shin, Leeiu Kim, Wookyung Lee, Eyee Hyun Nam, Seungmin Kim, Bryan S. Kim, Sungjin Lee, Eunji Lee |
| 2025 | Carbon-Aware Temporal Data Transfer Scheduling Across Cloud Datacenters. Elvis Rodrigues, Jacob Goldverg, Tevfik Kosar |
| 2025 | Causal Latency Modelling for Cloud Microservices. Christopher Lohse, Diego Tsutsumi, Amadou Ba, Pavithra Harsha, Chitra Subramanian, Martin Straesser, Marco Ruffini |
| 2025 | ClusterLink: Redefining Application Connectivity for the Multi-cloud Era. Kfir Toledo, Pravein Govindan Kannan, Michal Malka, Etai Lev-Ran, Or Ozeri, Vita Bortnikov, Ziv Nevo, Kathy Barabash |
| 2025 | Cost-Efficient VM Selection for Cloud-Based LLM Inference with KV Cache Offloading. Kihyun Kim, Jinwoo Kim, Hyunsun Chung, Myung-Hoon Cha, Hong-Yeon Kim, Youngjae Kim |
| 2025 | DNN-Adapt: Reinforcement Learning-Based Hybrid Batching for Efficient DNN Serving. Milind Varma, Sai Venkat Malreddy, Liting Hu |
| 2025 | Disk-Based Shared KV Cache Management for Fast Inference in Multi-Instance LLM RAG Systems. Hyungwoo Lee, Kihyun Kim, Jinwoo Kim, Jungmin So, Myung-Hoon Cha, Hong-Yeon Kim, James J. Kim, Youngjae Kim |
| 2025 | Dynamic In-node Group-Aware Scheduling for Multi-Tenant Machine Learning Services on Kubernetes. Peini Liu, Jordi Guitart |
| 2025 | ESTHER: Application-First Hardware-Level QoS-Enforcement for Cloud Native Environments. Oliver Larsson, Thijs Metsch, Cristian Klein, Erik Elmroth |
| 2025 | Efficient Microservice Monitoring Via Kernel Transformation and FFT Forecasting. Marianna Ojanen, Maryam Sabzevari, Sándor Szedmák |
| 2025 | Efficient Versioning for Unikernels. Gaulthier Gain, Benoit Knott, Laurent Mathy |
| 2025 | Energy-Aware Resource Allocation and Container Migration in Distributed Data Centers Under Variable Energy Pricing: A Genetic Programming Hyper-Heuristic Approach. Mathew Falloon, Hui Ma, Gang Chen |
| 2025 | EnergyLess: An Energy-Aware Serverless Workflow Batch Orchestration on the Computing Continuum. Reza Farahani, Radu Prodan |
| 2025 | Game-Theoretic Reinforcement Learning for Task Optimization Under Time-Sensitive Constraints. Emanuele Carlini, Patrizio Dazzi, Matteo Mordacchini |
| 2025 | HEART: Heterogeneous-Aware Traffic Allocation in Multi-Replica Deployments on Kubernetes. Hokun Park, Donggyun Kim, Hyungjun Kim, Gyujeong Lim, HeonChang Yu |
| 2025 | Helm-ET: Reducing Exposure to Lateral Movement in Kubernetes Artifacts. Jacopo Bufalino, Jose Luiz Martin Navarro, Aleksi Peltonen, Tuomas Aura |
| 2025 | HeteroScheduler: Dynamic Task Scheduling for CPU-GPU Optimization and Contention Mitigation in Cloud Data Centers. Seokwon Choi, Hyeonsang Eom |
| 2025 | HotSwap: Enabling Live Dependency Sharing in Serverless Computing. Rui Li, Devesh Tiwari, Gene Cooperman |
| 2025 | Is Your Cluster Truly Fully Loaded? Exploring Shadow Resources in Host State Synchronization. Jiawen Liu, Yuehao Xu, Zhijun Ding |
| 2025 | Korel: Mitigating Stragglers via Real-Time Automatic Mixed Precision in Distributed Deep Learning Environments. Hyunseung Jung, Hyungjun Kim, HeonChang Yu |
| 2025 | LLM-Powered Automated Cloud Forensics: From Log Analysis to Investigation. Dalal Alharthi, Rozhin Yasaei |
| 2025 | MOBOS: Co-Optimizing Cost and Execution Time in Serverless Workflow with Multi-Objective Bayesian Optimization. Minjae Kang, HeonChang Yu |
| 2025 | MSTH-Former: Optimizing Workload Prediction in Edge-Cloud Continuum with Multi-Scale Temporal and Hierarchical Knowledge Convergence and Distillation. Sharmen Akhter, Eui-Nam Huh |
| 2025 | Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference. Pol G. Recasens, Ferran Agullo, Yue Zhu, Chen Wang, Eun Kyung Lee, Olivier Tardieu, Jordi Torres, Josep Lluís Berral |
| 2025 | Multi-Agent Reinforcement Learning-Based In-Place Scaling Engine for Edge-Cloud Systems. Jovan Prodanov, Blaz Bertalanic, Carolina Fortuna, Shih-Kai Chou, Matjaz B. Juric, Ramon Sanchez-Iborra, Jernej Hribar |
| 2025 | Optimizing Receive Flow Steering for Mixed Traffic in High-Performance Cloud Datacenters. Junseo Jang, Jaehyun Hwang |
| 2025 | PROBA: Enhancing Serverless Edge Computing via Adaptive Task Scheduling and Probabilistic Resource Sharing. Manish Pandey, Byungchul Tak, Young-Woo Kwon |
| 2025 | Precomputation-Optimized Lakehouse Architecture for Online Analytical Processing Tasks. Haida Zhang, Lin Sun, Zhengtong Zhang, Jiayang Xia, Ziang Huang, Jiansi Wang, Haopeng Chen, Yan Jiao, Yongming Xu |
| 2025 | QPS- Fit: An Efficient and Performant Parallel Algorithm for Hybrid Optical and Packet Switching. Dongzhao Song, Jingfan Meng, Qianru Yu, Jun Jim Xu |
| 2025 | RACS-SADL: Robust and Understandable Randomized Consensus in the Cloud. Pasindu Tennage, Antoine Desjardins, Lefteris Kokoris-Kogias |
| 2025 | ReSACO: A Meta Reinforcement Learning Method for Fast Offloading in Mobile Edge Computing. Myeongjun Kim, HeonChang Yu |
| 2025 | Real-Time Interference-Aware CPU and I/O Capping Mechanism for Multi-Tenant Containers. MohammadReza HoseinyFarahabady, Albert Y. Zomaya |
| 2025 | Revisiting SQL Statement Logging for SQLite on AWS S3. Yewon Shin, Jonghyeok Park |
| 2025 | Routing Strategies for RoCE Networks in AI Clouds. Abdul Alim, Ali Sydney, Liran Schour, Abdullah Kayi, Laurent Schares, Pavlos Maniotis, Anand Singh, Bengi Karacali |
| 2025 | SLO-Aware Container Orchestration on Kubernetes Clusters. Angelo Marchese, Orazio Tomarchio |
| 2025 | Serverless Data Analytics (Finally) Bridging the Gap: Introducing the Ortzi DataFrame. Germán T. Eizaguirre, Marc Hostau, Marc Sánchez Artigas |
| 2025 | Speeding up Model Loading with Fastsafetensors. Takeshi Yoshimura, Tatsuhiro Chiba, Manish Sethi, Daniel G. Waddington, Swaminathan Sundararaman |
| 2025 | Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework. Julien Soulé, Jean-Paul Jamont, Michel Occello, Louis-Marie Traonouez, Paul Théron |
| 2025 | Temporal Fusion Transformer Based Vertical Scaling Management for Kubernetes. Kemalcan Bora, Elli Kartsakli, Eduardo Quiñones Moreno |
| 2025 | The IoT Whisperer: A Framework for Intelligent IoT Service Composition Through LLMs. Ewan Warburton, Abdessalam Elhabbash, Saad Ezzini, Yehia Elkhatib |
| 2025 | Towards Efficient Key-Value Cache Management for Prefix Prefilling in LLM Inference. Yue Zhu, Hao Yu, Chen Wang, Zhuoran Liu, Eun Kyung Lee |
| 2025 | Towards Secure Cloud-Native Computing: Unveiling Kubernetes Misconfigurations with Large Language Models. Mostafa Anouar Ghorab, Mohamed Aymen Saied |
| 2025 | TraceWizard: End-to-End Distributed Tracing Across Host and Network Devices in Cloud. Kuangyuan Li, Jingrun Zhang, Pengfei Chen, Hongyang Chen, Ruipeng Hong, Wanqi Yang, Chen Sun |
| 2025 | Universal Workers: A Vision for Eliminating Cold Starts in Serverless Computing. Saman Akbari, Manfred Hauswirth |
| 2025 | ZipNN: Lossless Compression for AI Models. Moshik Hershcovitch, Andrew Wood, Leshem Choshen, Guy Girmonsky, Roy Leibovitz, Or Ozeri, Ilias Ennmouri, Michal Malka, Sang (Peter) Chin, Swaminathan Sundararaman, Danny Harnik |