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AIMM-Edge 2026 : AIMM-Edge 2026: Agentic and AI-Native Media Delivery over Edge-Cloud

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Link: https://aimm-edge2026.scc.lancs.ac.uk/
 
When Oct 30, 2026 - Oct 30, 2026
Where Madrid
Submission Deadline Aug 15, 2026
Notification Due Sep 11, 2026
Final Version Due Sep 18, 2026
 

Call For Papers

First Workshop on AI-Native Media Delivery over Edge-Cloud Systems. Co-located with
CNSM 2026, Alcala de Henares (Madrid), Spain.

AIMM-Edge 2026 invites research and operational experience papers on AI-native
management, orchestration, optimisation, and observability for next-generation
Internet media delivery systems spanning transport, edge-cloud platforms, CDN
coordination, QoE optimisation, and autonomous operational control.

The workshop aligns with CNSM 2026 interests in service management, programmable
infrastructure, AI-native operations, observability, security, and sustainability, while
keeping a strong focus on deployable, measurable, and operationally grounded media
delivery research.

Topics include, but are not limited to:
• Low-latency media delivery and adaptive streaming, HTTP/3, QUIC,
WebTransport, and transport evolution
• Multi-CDN coordination, caching, and content steering
• Edge-cloud orchestration and compute-aware delivery
• QoE-aware optimisation and closed-loop control
• AI-native operational management and orchestration
• Interactive, immersive, and personalised media systems
• Observability, benchmarking, privacy, and security
• Sustainability and energy-aware media delivery

Submission Information
• Paper length: maximum 6 pages, including references, aligned with CNSM
workshop policy
• Publication: accepted papers submitted for inclusion in IEEE Xplore, subject to
CNSM policies

Important Dates
• Workshop call for papers due: June 29, 2026
• Workshop papers submission deadline: August 14, 2026
• Notification of acceptance: September 11, 2026
• Camera-ready deadline: September 18, 2026

Organisers & Contacts
• Yehia Elkhatib, Glasgow University
• Nicholas Race, Lancaster University
• Edward Austin, Lancaster University
• Rajiv Ramdhany, BBC R&D


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