Workshop on Computing Networks
Computing networks combine communication and computing resources to acquire, transmit, process and act upon data, often under delay, computational and bandwidth constraints, and with stringent performance, resilience and security requirements. They may include middleboxes for performing various functionalities, including in-network processing, executing network functions, potentially in complex topologies, with an emphasis on the interplay between computing and communication, and the resulting services and functionality. Due to limited resource availability, one needs to jointly consider computing and networking resources to optimize end-to-end performance. Computing networks will play an essential role in fixed and mobile communication networks, and will also be crucial in future industrial control systems, transportation, smart environments, and digital manufacturing.
The aim of the workshop is to bring together researchers working on theoretical and systems aspects of computing networks, with an emphasis on novel networking architectures and algorithms that support computing and on computing architectures and algorithms that can adapt to the network.
The workshop invites both theoretical and experimental contributions, the topics of interest include but are not limited to:
- Network and computing architectures for computing systems (SDN, NFV, cloud infrastructures)
- Service and function chaining
- Stochastic models for computing networks
- Game theoretical models and economics of computing networks
- Resource management for computing networks
- Measurement studies of computing networks
- Network-aware algorithm design
- Algorithm-aware network design
- Protocol support for computing networks
- Algorithmic support for computing networks
- Applications of computing networks (smart grids, autonomous driving, smart manufacturing, etc)
Important Dates
Paper submission deadline: March 1, 2017
Workshop: June 15, 2017
Organizing committee
Co-chairs:
György Dán (KTH Royal Institute of Technology)
Markus Fidler (Leibniz Universität Hannover)
