This workshop intends to stimulate discussion about these new frontiers of sustainable networking. The workshop does not aim at covering the very vast range of applications of ML in networking, or IoT technologies, but focuses on tools, technologies, paradigms and solutions that target network sustainability. These include smart resource allocation over multi-dimensional decision spaces, the prediction of traffic, channel conditions, energy that can be harvested from the environment, energy savings can be enabled on the different system and operation levels.
The First Workshop on Sustainable networking through MachIne Learning and Internet of thiNGs SMILING 2019 in conjunction with IEEE INFOCOM 2019
April 29 – May 2, 2019, Paris, France
Scope
Sustainability is a key challenge of the digitalized world and, while technologies for the connected world evolve, sustainability calls for new paradigms and solutions. The research in the field of sustainable networking has been vibrant for some years and now new frontiers in this topic are emerging. In the application domain, this is the IoT momentum and the research is boosted by several paradigms, among which are the Smart City, 5G and Industry 4.0. When thousands or millions or devices will be deployed, IoT systems will need an architecture lasting in time, saving the device batteries and reducing the cumulative energy cost for running the system and the applications. In the methodological domain, planning, developing and managing complex and massive systems of devices, that might also be IoT devices, Machine Learning (ML) is emerging as the technology of choice.
This workshop intends to stimulate discussion about these new frontiers of sustainable networking. The workshop does not aim at covering the very vast range of applications of ML in networking, or IoT technologies, but focuses on tools, technologies, paradigms and solutions that target network sustainability. These include smart resource allocation over multi-dimensional decision spaces, the prediction of traffic, channel conditions, energy that can be harvested from the environment, energy savings can be enabled on the different system and operation levels.
The scope of the workshop includes but is not limited to the following topics
ML for resource management and network optimization
ML for energy harvesting and energy consumption modeling
Energy efficient protocol design using ML
Experiences in applying ML in sustainable networking
Low-power local and wide-area networks
Energy harvesting and wireless power transfer
Low energy data processing, analysis and storage for the IoT
Sustainability issues in IoT sensors and communication platforms
Methods and architectures for local edge and fog computing for IoT
Green IoT metrics, performance, measurement, test-beds and results
WORKSHOP SCHEDULE
Submission deadline: December 30, 2018
Acceptance notification: February 22, 2019
Camera ready: March 10, 2019
Instructions for authors are here: http://infocom2019.ieee-infoco...
Submit your paper at: https://edas.info/newPaper.php...
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