Exploiting Reliable and Scalable Multicast Services in IaaS Datacenters
| Autor: | Junjie Xie, Bangbang Ren, Deke Guo, Jie Wu, Honghui Chen, Tao Chen |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Service (systems architecture)
Information Systems and Management Multicast Computer Networks and Communications business.industry Computer science Quality of service 020206 networking & telecommunications 02 engineering and technology Computer Science Applications Hardware and Architecture Server Scalability Reliable multicast 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Unicast business REMUS Computer network |
| Zdroj: | IEEE Transactions on Services Computing. 14:1370-1383 |
| ISSN: | 2372-0204 |
| DOI: | 10.1109/tsc.2018.2877733 |
| Popis: | A large number of servers are interconnected using a specific datacenter network to deliver the infrastructure as a service (IaaS). Multicast can jointly utilize the network resources and further reduce the consumption of network bandwidth more than individual unicast. The source of a multicast service, however, does not need to be in a specific location as long as certain constraints are satisfied. This means the multicast can have uncertain sources, which could reduce the network resource consumption more than a traditional multicast service and further improve the quality of service. In this paper, we propose a novel reliable multicast service with uncertain sources named ReMUS. The goal is to minimize the sum of the transfer cost and the recovery cost, although finding such a ReMUS is very challenging. Thus, we design a source-based multicast method to solve this problem by exploiting the flexibility of sources when no recovery nodes exist in the network. Furthermore, we design a general multicast method to jointly exploit the benefits of uncertain sources and recovery nodes to minimize the total cost of ReMUS. We conduct extensive evaluations under Internet2 and datacenter networks. The results indicate that our methods can efficiently realize the reliable and scalable multicast with uncertain sources, irrespective of the settings of networks and multicasts. To the best of our knowledge, we are the first to study the reliable multicast service under uncertain sources. |
| Databáze: | OpenAIRE |
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