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Restoration methods for cloud multicast virtual networks

机译:云组播虚拟网络的恢复方法

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Providing reliability guarantees for services hosted in cloud data center networks is a well studied problem that received much attention from the literature in recent years. Yet, the existing literature failed to account for the mode of communication that these hosted services may exhibit. Rather, it is assumed that the constituent Virtual Machines (VMs) are always exchanging traffic in a one-to-one communication mode. This paper is concerned with the problem of restoring failed services with a one-to-many communication mode, the mode of communication for a multitude of multicast applications and services hosted today in the cloud. Through motivational examples we show that the problem of restoring multicast Virtual Networks (VNs) greatly differs from that of unicast services, thereby demanding separate attention. To this extent, we formally define the problem of restoring multicast services in event of facility node failure, and we mathematically formulate it using an Integer Linear Programming (ILP) model. Further, we propose REAL: a multicast virtual network re storation al gorithm. REAL distinguishes the failure of multicast source node from that of multicast terminal nodes, and adopts a hop-to-hop search to handle receiver or terminal node failures, and a path convergence approach to recover from source node failures. We evaluate our proposed schemes against a Greedy and a Steiner-based restoration schemes, and we show that our suggested method outperforms its peers in terms of restoration ratio and total achievable revenue.
机译:为云数据中心网络中托管的服务提供可靠性保证是一个经过充分研究的问题,近年来受到文献的广泛关注。但是,现有文献未能解释这些托管服务可能表现出的通信方式。而是假设组成虚拟机(VM)始终以一对一的通信模式交换流量。本文关注的问题是使用一对多通信模式还原失败的服务,这是当今托管在云中的大量多播应用程序和服务的通信模式。通过激励性示例,我们表明,还原多播虚拟网络(VN)的问题与单播服务存在很大差异,因此需要单独注意。在此程度上,我们正式定义了在设施节点发生故障时恢复多播服务的问题,并使用整数线性规划(ILP)模型对其进行数学表示。此外,我们提出了REAL:多播虚拟网络存储算法。 REAL将组播源节点的故障与组播终端节点的故障区分开来,并采用逐跳搜索来处理接收方或终端节点的故障,并采用路径收敛方法从源节点故障中恢复。我们针对基于贪婪和基于Steiner的恢复方案评估了我们提出的方案,并且表明了我们提出的方法在恢复率和可实现的总收入方面均优于同类方案。

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