The power of communications: what's the energy footprint of the Web?
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This is a short version of my keynote presentation at the IoT event (http://iotevent.eu/) on the prospects of Future Internet research. What's the energy footprint of the Web? Is the current Web growth sustainable? How could we re-design the internet to become more energy efficient? I advocate a more closer collaboration between energy experts and communication engineers to come up with an "Internet of Energy", where information flows alongside energy and the one resonates with the other.
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The power of communications: what's the energy footprint of the Web?
- 1. The Power of Communications Prof. Antonio Liotta Eindhoven University of Technology http://bit.ly/autonomic_networks Twitter: a_liotta
- 2. The shape of the Web to come Prof. A.Liotta Slide 1
- 3. A feel of the current Web footprint Prof. A.Liotta Slide 2
- 4. How dirty is your data? Prof. A.Liotta Slide 3
- 5. Web energy demand forecast (2020) Prof. A.Liotta Slide 4
- 6. Energy requirements at the edge (2020) Each ~100 mWatt transmission power Each 1 Gigawatt supply Prof. A.Liotta Slide 5
- 7. To turn data into usable knowledge we must find efficient ways to move it around Prof. A.Liotta Slide 6
- 8. Today: a complex system operated simplistically (overprovisioning) Over-dimensioned Over-dimensioned No idea whether servers data flows user is satisfied Over-provisioned Over-specified networks terminals Prof. A.Liotta Slide 7
- 9. Future Internet meets the definition of “complexity” set by “complexity theory” • Properties of whole can’t be inferred from properties of individual parts • Individual components interact nonlinearly, leading to emergent behavior • Constantly evolves and unfolds over time Prof. A.Liotta Slide 8
- 10. Natural networks work thanks to adaptivity and learning Eminent examples: • Human brain • Immune system • Ecosystems • Insect colonies • Most social structures • … Brain synapses (Source: www.chiefscientist.gov.au) Prof. A.Liotta Slide 9
- 11. We know how to build learning robots. But networks can learn too Original Clips 50 50 100 100 150 150 200 Difference in 250 200 250 Temporal 300 300 350 350 Motion 400 400 450 450 500 500 550 550 100 200 300 400 500 600 700 100 200 300 400 500 600 700 Initially we train the Reinforcement Learning network to handle teaches how to handle “News over Laptop” “Sport over Phone” Prof. A.Liotta Slide 10
- 12. Cognitive networks will make sense of diverse perturbations „Sport over mobile phone‟ QoS probe actuators Optimizing QoE Machine QoE measure QoS prediction Learning or inference Prof. A.Liotta Slide 11
- 13. DEMANES: The first ARTEMIS IoT project (Design, Monitoring and Operation of Adaptive Networked Embedded Systems) Prof. A.Liotta Slide 12 www.demanes.eu
- 14. Adaptivity & learning to tackle the diversity of IoT Requirements Models and languages for adaptive systems Adaptive system Verification Self-optimization composition and testing Prof. A.Liotta Slide 13 www.demanes.eu
- 15. DEMANES Pilots (focus on autonomic modeling and operation) Smart Safe and Smart Airport Cooperating Secure urban Management Sensors at transport and Home environment Prof. A.Liotta Slide 14 www.demanes.eu
- 16. Internet of Energy: energy flows alongside the information flow Prof. A.Liotta Slide 15
- 17. Thank you ! More about my work http://bit.ly/autonomic_networks In the press http://bit.ly/press_articles “All of YouTube through a 40-year-old funnel” bit.ly/Volkskrant-EN bit.ly/booklet-antonio bit.ly/pervasive-networks Prof. A.Liotta Slide 16