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Network functions virtualization with soft real-time guarantees

机译:网络功能虚拟化和软实时保证

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Network functions are increasingly being commoditized as software appliances on off-the-shelf machines, popularly known as Network Functions Virtualization (NFV). While this trend provides economics of scale, a key challenge is to ensure that the performance of virtual appliances match that of hardware boxes. We present the design and implementation of NFV-RT, a system that dynamically provisions resources in an NFV environment to provide timing guarantees. Specifically, given a set of service chains that each consist of some network functions, NFV-RT aims at maximizing the total number of requests that can be assigned to the cloud for each service chain, while ensuring that the assigned requests meet their deadlines. Our approach uses a linear programming model with randomized rounding to efficiently and proactively obtain a near-optimal solution. Our simulation shows that, given a cloud with thousands of machines and service chains, NFV-RT requires only a few seconds to compute the solution, while accepting three times the requests compared to baseline heuristics. In addition, under some special settings, NFV-RT can provide significant performance improvement. Our evaluation on a local testbed shows that 94% of the packets of the submitted requests meet their deadlines, which is three times that of previous reactive-based solutions.
机译:网络功能越来越多地作为现成机器上的软件设备商品化,通常被称为网络功能虚拟化(NFV)。尽管这种趋势提供了规模经济效益,但关键的挑战是确保虚拟设备的性能与硬件设备的性能相匹配。我们介绍了NFV-RT的设计和实现,这是一个在NFV环境中动态配置资源以提供时序保证的系统。具体来说,给定一组服务链,每个服务链都包含一些网络功能,NFV-RT的目的是在确保分配的请求能够满足其截止日期的同时,最大化可为每个服务链分配给云的请求总数。我们的方法使用带有随机舍入的线性规划模型来高效主动地获得近似最优的解决方案。我们的仿真表明,在云中有成千上万的机器和服务链的情况下,NFV-RT只需几秒钟即可计算解决方案,而接受的请求是基准启发式算法的三倍。此外,在某些特殊设置下,NFV-RT可以显着提高性能。我们在本地测试平台上的评估显示,已提交请求的数据包中有94%符合其期限,这是以前基于响应式解决方案的三倍。

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