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Deutsches
Forschungsnetz
Science engagement round table
DFN –Deutsches Forschungsnetz
Overview
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DFN network
DFN organization
Subscriber relations
Partner relations
Direct science outreach
Lessons learned
Outlook
DFN Network
Planned Topology 2016
IP Platform external connections
Growth in Traffic
• Moderate traffic growth currently
• Strong traffic growth forecast, caused by new projects
– However: precise timing is still uncertain
• Peak-Data rates are growing through local infrastructure improvements
Data Volume Imported [T-Byte]
2013 - 2015
30000
25000
20000
15000
10000
5000
0
APRIL 2013
OCTOBER 2013
APRIL 2014
OCTOBER 2014
APRIL 2015
Growth in Subscribers
Number of Subscribers
800
700
600
500
400
300
200
100
0
2007
2015
Subscriber community
• Many subscribers are members, but not required
• Typical DFN subscribers:
– High-end HPC sites (e.g. Gauss Centres)
– Leading research and processing centres
– Research societies (e.g. Helmholtz, Max Planck,
Fraunhofer)
– Universities and other education orgs
Trust in subscriber relations
• DFN subscriber/member outreach:
– Bi-annual membership meetings
– Bi-annual workshops for subscriber IT
– Several other specialist committees
• Trusted subscriber representatives
– Named individuals authorized to command
modifications to network settings (e.g. DDOS cases)
– Certificated Services
• Strong bottom-up feedback and accountability
Partner community
• Partners in the networking community:
– European and overseas NRENs
– GÉANT
– International twinning partners (e.g. KENET)
• Collaboration activities:
– GNx projects bring people from partners together
• Cross-domain networking performance
– PerfSONAR
– eduPERT
– mdVPN
Direct outreach to scientists
• "X-WiNner award" for young researchers
– Rewards excellence in use of networking for science
• Enlighten your Research Global
– DFN partner in 2015 round
– Latest initiative to involve scientists
– Use cases for driving science with network services
Lessons learned
• Context:
– Distributed science activities are growing fast
– Science data volumes are growing even faster
– Network usage patterns differ between disciplines
• Conclusions drawn:
– Need more granular understanding of varying
networking requirements
– Need to develop a more interactive model of
network service provision, oriented to those
requirements
Outlook
• Keep building an outstanding network
– BUT ALSO –
• Understand needs of different science communities
• Promote the network capabilities to scientists
• Network efficiency, help remove bottlenecks on the
WHOLE end-to-end path (scientist to scientist)
• Provide tools that facilitate adoption of best practices
Thank You