Delay-Optimized Multicast Tree Packing in Software-Defined Networks

In traditional networks, the multicast tree packing solutions usually aim to minimize the overall multicast tree cost, which can effectively improve network accommodation capacity but is disadvantageous to fully use network resources. In this article, we propose a delay-optimized multicast tree pack...

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Vydané v:IEEE transactions on services computing Ročník 16; číslo 1; s. 261 - 275
Hlavní autori: Zhang, Xinchang, Wang, Yinglong, Geng, Guanggang, Yu, Jiguo
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1939-1374, 2372-0204
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Shrnutí:In traditional networks, the multicast tree packing solutions usually aim to minimize the overall multicast tree cost, which can effectively improve network accommodation capacity but is disadvantageous to fully use network resources. In this article, we propose a delay-optimized multicast tree packing problem called delivery delay minimized multicast tree packing (DDMMTP), which aims to minimize the average source-destination delay, under constraints on the bandwidth and maximum source-destination delay, according to available network resources. A low source-destination delay is desirable because it improves the service quality, especially for time-sensitive applications. In practice, the DDMMTP is highly valuable for the software-defined network (SDN) mainly because this new network paradigm has the ability to rapidly rearrange multicast routes on demand. The DDMMTP problem is NP-hard. We solve it approximately by a batched multicast tree packing algorithm and a network accommodation capacity improvement algorithm that adjusts existing multicast paths on demand. We also propose a source-destination delay improvement algorithm to further reduce source-destination delays based on new available network resources.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:1939-1374
2372-0204
DOI:10.1109/TSC.2021.3106264