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Source-Coded Multicast With Single and Aggregated Sources for Efficient Content Delivery

delete2024-01-01
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OA
AI
T
Tomás Lestayo Martínez *
M
Manuel Fernández‐Veiga *
DOI:10.1109/OJCOMS.2024.3460422delete
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摘要

摘要

En 中文
Multicast transmission is the natural approach to efficiently transport data from a source to multiple receivers using minimum network bandwidth. Two incompatible options exist to realize this multicast support: the classical one is the design and deployment of a specific multicast routing protocol at the network layer, and the other one is the shift toward a network-coding solution where the routers encode incoming packets into algebraic structures before forwarding them to the next hop. Both alternatives involve practical complexities that have hindered their adoption at a large scale in content delivery networks (CDN) due to their signaling overhead, but mainly because in both cases the network must adhere to an all-or-nothing behavior: either all the routers follow the rules of the data and control planes, or the schemes fail to work globally. In this paper, we propose Source-Coded Multicast (SCM), a novel technique for content delivery in multicast networks that uses the network bandwidth efficiently while requiring encoding operations only at the source node. Thus, SCM does not rely on a strict multicast routing protocol nor on re-encoding algorithms at the routers, so it is both practical and useful for CDNs and other applications. We further extend the approach to aggregated sources, i.e., multiple multicast sources with partially overlapped distribution trees. Our numerical results show that SCM is optimal or nearly optimal in a large fraction of network topologies, and overcomes the complexity of legacy IP-based multicast and network coding.
Keyword:
Encoding
Receivers
Network coding
Network topology
Routing protocols
Bandwidth
Complexity theory
Multicast
source-coded
network coding
content distribution network

期刊

I
IEEE Open Journal of the Industrial Electronics Society
IF:
4.3
论文数:
1.7K
被引数:
991

机构

U
Universidade de Vigo
学者数:
7.7K
论文数: 8.3K
被引数: 13
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