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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Self-Adaptive Systems Challenges in Delivering Object-Based Media
AU - Porter, Barry
AU - Dean, Paul
AU - Race, Nicholas
AU - Lomas, Mark
AU - Ramdhany, Rajiv
PY - 2024/12/2
Y1 - 2024/12/2
N2 - Multi-agent, decentralised, and collective self-adaptive systems have been studied in a range of domains from smart-cities to the social dynamics of organisations. We present a novel application for research in this area, with the emerging distributed systems field of object-based media. Unlike traditional media, which is delivered over the Internet as pre-encoded compressed video segments, object-based media divides a media experience into its constituent parts, such as presenters, actors, backgrounds, and information overlays. These elements are then rendered and composited on-demand for each user, to support highly customisable experiences. We analyse the distributed systems challenges of delivering object-based media in terms of self-adaptive systems, and present work on the prototype technology we are using to explore potential solutions.
AB - Multi-agent, decentralised, and collective self-adaptive systems have been studied in a range of domains from smart-cities to the social dynamics of organisations. We present a novel application for research in this area, with the emerging distributed systems field of object-based media. Unlike traditional media, which is delivered over the Internet as pre-encoded compressed video segments, object-based media divides a media experience into its constituent parts, such as presenters, actors, backgrounds, and information overlays. These elements are then rendered and composited on-demand for each user, to support highly customisable experiences. We analyse the distributed systems challenges of delivering object-based media in terms of self-adaptive systems, and present work on the prototype technology we are using to explore potential solutions.
U2 - 10.1109/ACSOS61780.2024.00037
DO - 10.1109/ACSOS61780.2024.00037
M3 - Conference contribution/Paper
SN - 9798350363883
BT - 2024 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)
PB - IEEE
ER -