SubsidieMeestersCache-aided Folding for Reducing VoD Loads in Networks
This project aims to implement a novel caching method to reduce video-on-demand costs and improve network performance through algorithmic exploration and practical testing.
Projectdetails
Introduction
Communicating video-on-demand (VoD) over various networks is very costly. VoD drives up the costs for purchasing bandwidth and overprovisioning infrastructures, as well as the costs to content providers (Netflix, Amazon, etc.) that must pay large fees to network operators to deliver content to their clients.
Problem Statement
To reduce the massive VoD fees, networks employ caches. Our findings in our ERC project DUALITY reveal a new method of exploiting caches that boosts the performance of various networks.
Project Goals
We wish to explore the practical ramifications of these findings in practical networks. This project will explore the algorithmic and testing work needed to render these ideas practical.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 150.000 |
| Totale projectbegroting | € 150.000 |
Tijdlijn
| Startdatum | 1-3-2023 |
| Einddatum | 31-8-2024 |
| Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- EURECOM GIEpenvoerder
Land(en)
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Commoditizing Data Analytics in the Cloud
Develop an open, cost-efficient cloud analytics database, CODAC, to reduce query costs and enable seamless data migration across platforms, enhancing large-scale data analytics accessibility.
Goal-Oriented Networking for Space
The project aims to enhance space communication networks by developing goal-oriented methods for efficient data flow management, enabling scalable interplanetary connectivity with reduced resource usage.
Distributed Coordinated Access Point
This project aims to validate a low-cost, ultra-reliable Cell Free massive MIMO solution using synchronized Wi-Fi 6 access points for low-latency communication and scalability.
Computing Nonlinear Functions over Communication Networks
SENSIBILITÉ develops a novel theory for efficient distributed computing of nonlinear functions over networks, aiming to enhance scalability and performance in real-world applications.
Reinventing Multiterminal Coding for Intelligent Machines
IONIAN aims to revolutionize cooperative perception in intelligent machines by developing a multiterminal coding paradigm that enhances data compression and communication for safer autonomous navigation.
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Solving the ‘last-mile delivery challenge’ for quality Over-The-Top (OTT) streaming content
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Surelock
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