IEEE International Conference on Cloud Networking
8–10 November 2021 // Virtual Conference

Technical Program

Monday, November 8 – 10:00 – 11:15

S1: Machine Learning for Cloud Computing

S1.1 Leveraging Partial Model Extractions using Uncertainty Quantification
Arne Aarts (Eindhoven University of Technology, The Netherlands); Wil Michiels (NXP Semiconductors, The Netherlands); Peter Roelse (Irdeto BV, The Netherlands)

S1.2 Using Machine Learning and In-band Network Telemetry for Service Metrics Estimation
Leandro Almeida (Instituto Federal de Educação, Ciência e Tecnologia da Paraíba, Brazil); Rafael Pasquini (Federal University of Uberlândia – UFU, Brazil); Fábio Luciano Verdi (Federal University of São Carlos, Brazil)

Monday, November 8 – 11:30 – 13:00

S2: Edge Computing

S2.1 (Short Paper) DFaaS: Decentralized Function-as-a-Service for Federated Edge Computing
Michele Ciavotta (University of Milano-Bicocca, Italy); Davide Motterlini (University of Milano – Bicocca, Italy); Marco Savi (University of Milano-Bicocca, Italy); Alessandro Tundo (University of Milano – Bicocca, Italy)

S2.2 Enabling Delay-Sensitive IoT Application by Programmable Local 5G Edge
Koichiro Amemiya (Fujitsu Limited, Japan); Akihiro Nakao (The University of Tokyo, Japan)

S2.3 A Global Orchestration Matching Framework for Energy-Efficient Multi-Access Edge Computing
Tobias Mahn and Anja Klein (TU Darmstadt, Germany)

Monday, November 8 – 15:00 – 16:00

S3: Video Streaming

S3.1 Super-resolution on Edge Computing for Improved Adaptive HTTP Live Streaming Delivery
João da Mata Libório, Filho, Maiara de S. Coelho and Cesar A. V. Melo (Federal University of Amazonas, Brazil)

S3.2 An Edge Video Analysis Solution For Intelligent Real-Time Video Surveillance Systems
Alessandro Souza Silva (Universidade Federal do Ceará, Brazil); Michel S. Bonfim (Universidade Federal do Ceara, Brazil); Paulo A. L. Rego (Federal University of Ceará, Brazil)

Tuesday, November 9 – 11:30 – 13:00

S4: Telemetry and Benchmarking

S4.1 Understanding and Leveraging Cluster Heterogeneity for Efficient Execution of Cloud Services
Sambit K Shukla (University of California Davis, USA); Dipak Ghosal and Matthew Farrens (University of California, Davis, USA)

S4.2 Estimating Function Completion Time Distribution in Open Source FaaS
Dávid Balla, Markosz Maliosz and Csaba Simon (Budapest University of Technology and Economics, Hungary)

Tuesday, November 9 – 15:00 – 16:00

S5: Cloud Networking

S5.1 Longer Stay Less Priority: Flow Length Approximation Used In Information-Agnostic Traffic Scheduling In Data Center Networks
Muhammad Shahid Iqbal (National Yang-Ming Chiao Tung University, Taiwan); Chien Chen (National Yang Ming Chiao Tung University, Taiwan)

S5.2 Where is the Light(ning) in the Taproot Dawn? Unveiling the Bitcoin Lightning (IP) Network
Pedro Casas (Austrian Institute of Technology (AIT), Austria); Matteo Romiti and Peter Holzer (Austrian Institute of Technology, Austria); Sami Ben Mariem (Université de Liège, Belgium); Benoit Donnet (Université de Liège (ULg), Belgium); Bernhard Haslhofer (Austrian Institute of Technology, Austria)

S5.3 Throughput Distribution and Stabilization on TCP BBR Connections
Kohei Ogawa, Kouto Miyazawa, Saneyasu Yamaguchi and Aki Kobayashi (Kogakuin University, Japan)

S5.4 Characterizing Network Performance of Single-node Large-scale Container Deployments
Conrado Santos Boeira (Pontifical Catholic University of Rio Grande do Sul, Brazil); Miguel Neves (Dalhousie University, Canada); Tiago Ferreto (Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Brazil); Israat Haque (Dalhousie University, Canada)

Wednesday, November 10 – 11:30 – 13:00

S6: Efficient Resource Allocation

Using Distributed Tracing to Identify Inefficient Resources Composition in Cloud Applications
Clément Cassé (CNRS/LAAS – Université de Toulouse & Orange, France); Pascal Berthou (CNRS/LAAS – Université de Toulouse, France); Philippe Owezarski (LAAS-CNRS, France); Sébastien Josset (Orange, France)

A Machine Learning Approach for Service Function Chain Embedding in Cloud Datacenter Networks
Tom Jenno Wassing (University of Amsterdam, The Netherlands); Danny De Vleeschauwer (Nokia, Belgium); Chrysa Papagianni (University of Amsterdam, The Netherlands)

Profit-aware Placement of Multi-flavoured VNF Chains
Federica Paganelli (University of Pisa, Italy); Paola Cappanera (University of Florence, Italy); Antonio Brogi and Riccardo Falco (University of Pisa, Italy)

Wednesday, November 10 – 14:00 – 15:00

S7: Security

S7.1 Secured Distributed Storage Resource Allocation on Cloud-Edge Infrastructures
Konstantinos Kontodimas and Polyzois Soumplis (National Technical University of Athens, Greece); Aristotelis Kretsis (NTUA, Greece); Panagiotis Kokkinos (National Technical University of Athens & University of Peloponnese, Greece); Emmanouel Varvarigos (National Technical University of Athens & Computer Technology Institute, Greece)

S7.2 Mitigation of DNS Water Torture Attacks within the Data Plane via XDP-Based Naive Bayes Classifiers
Nikos Kostopoulos, Stavros Korentis, Dimitris Kalogeras and Vasilis Maglaris (National Technical University of Athens, Greece)

Wednesday, November 10 – 15:00 – 16:00

S8: Scheduling

S8.1 GDSim: Benchmarking Geo-Distributed Data Center Schedulers
Daniel Alves and Katia Obraczka (University of California, Santa Cruz, USA); Abdul Kabbani (Facebook, USA)

S8.2 Efficient Batch Scheduling of Large Numbers of Cloud Benchmarks
Derek Phanekham, Troy Walker and Suku Nair (Southern Methodist University, USA); Mike Truty (Google LLC, USA & Southern Methodist University, USA); Manasa Chalasani and Rick Jones (Google LLC, USA)