Virtualized End-to-End Management Functions for Aggregated Control of Video Traffic Flows
| Autor: | Kaliappa Ravindran, Ancy Cherian, Arun Adiththan |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
010302 applied physics
Access network business.industry Computer science Quality of service Node (networking) 020206 networking & telecommunications 02 engineering and technology Virtualization computer.software_genre 01 natural sciences End-to-end principle 0103 physical sciences Scalability 0202 electrical engineering electronic engineering information engineering Additive increase/multiplicative decrease Overhead (computing) business computer Computer network |
| Zdroj: | Q2SWinet@MSWiM |
| DOI: | 10.1145/3267129.3267142 |
| Popis: | The paper describes the management and control (M&C) functions of various network nodes in an end-to-end rate-adaptive video transport system. Mobile user devices download video clips by sharing the underlying network path from an ingress node. At the core software level, M&C functions realize the well-known AIMD (additive increase multiplicative decrease) based video rate control algorithm to handle congestion along the path. AIMD is exercised on the aggregated data flows at a source ingress node based on the 'loss reports' signaled from the receiver egress node. Our aggregated AIMD-based control reduces the signaling overhead, relative to the existing approaches that anchor an AIMD instance on each user device itself. This offers scalability, while improving the user-experienced QoS: such as low jitter in transfer rates and isolation against device faults. The offloading of aggregated AIMD-based control to the in-network overlay nodes also allows a reduction in the overall bandwidth usage. The software handling of 'last-mile' issues in the path between user devices and egress nodes (such as greedy users and access network channel sharing) are discussed, in a context of fine-granular video encoders in the devices. The paper also shows a virtualization of our M&C functions (as VNF modules) for deployment in large-scale video distribution networks --- such as YouTube. |
| Databáze: | OpenAIRE |
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