Combining networkfunctions Virtualization (NFV) with Software-Defined networking (SDN) is an emerging and promising solution to provide scalable and elastic network control and service. In such a system, virtualized ...
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Combining networkfunctions Virtualization (NFV) with Software-Defined networking (SDN) is an emerging and promising solution to provide scalable and elastic network control and service. In such a system, virtualized networkfunctions (NFs) need to be consistently migrated from one instance to another for various purposes, such as resource optimization, fault tolerance, load balancing, etc. These migrations involve simultaneously coordinating updates to the NF state and SDN forwarding state. To solve this problem, we design two consistent NF state update schemes: a controller-forwarding based scheme and a tagging-based scheme. Through analysis of the update process, we demonstrate that they both guarantee loss-free and order-preserving migrations. We further implement a prototype and carry out experiments with diverse traffic settings. Results demonstrate that the controller-forwarding based solution achieves 77 percent migration time compared with the state-of-the-art solution OpenNF, while correcting an error of it. Moreover, the tagging-based solution not only achieves 4.4 percent migration time, but also reduces up to 75 percent controller overhead compared with OpenNF at the cost of adding a tag in the unused fields of packet header.
Service function (SF) chaining enables network operators and infrastructure providers to flexibly orchestrate virtualized networkfunctions (NFs) at various places on software defined virtual networks. Meanwhile, with...
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ISBN:
(纸本)9781538634165
Service function (SF) chaining enables network operators and infrastructure providers to flexibly orchestrate virtualized networkfunctions (NFs) at various places on software defined virtual networks. Meanwhile, with the rapid prevalence of Internet-of-Things (IoT) applications and mobile network services, quality-of-service (QoS) requirements are getting increasingly diverse and network traffic volume and pattern are varying rapidly. The time-varying network traffic requires the infrastructure provider to dynamically adjust the appropriate amount of computational resources (e.g. CPU) assigned to an NF to efficiently process the traffic in the SF chaining infrastructure. In this paper, to adequately allocate CPU resources (available in limited amount) to virtual networks (VNs) requiring to satisfy diverse QoS levels in response to traffic variation without manual operations, we propose autonomic arbitration of CPU resources along SF chains which combines two CPU resource adjustment methods: The first method performs resource arbitration among VNs within a node, and the second method migrates NFs among nodes within a VN. These methods autonomically adjust the amount of CPU resource allocated to each NF so that over utilization of CPU can be avoided as much as possible. Moreover, during the autonomic resource adjustments in SF chains, the proposed methods are able to maintain communication paths on the substrate network so that the service is not interrupted at all. We also propose differentiated resource allocation for QoS differentiation and transferable resource searching. Through computer simulation, we verify that our autonomic resource adjustment methods can reduce the occurrence of CPU-saturation by more than 90%.
Service function chains (SFCs) are sequences of networkfunctions that provide specific services to meet operators' needs in today's ISPs and datacenter networks. To improve the performance of SFCs, programmab...
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Service function chains (SFCs) are sequences of networkfunctions that provide specific services to meet operators' needs in today's ISPs and datacenter networks. To improve the performance of SFCs, programmable data planes are used to leverage their low latency and high performance packet processing. However, SFCs need to be adaptable to dynamics such as changes in requirements and attributes. Therefore, the ability to migrate SFCs is essential. Unfortunately, migrating SFCs in distributed programmable data planes is challenging due to the risk of degraded performance and failure to meet SFCs requirements and resource constraints in switches. In this paper, we propose Monte, which provides an effective SFCs migration scheme in distributed programmable data planes. We build a novel integer programming model to represent the migration process with constraints on resource limitations of switches and SFCs attributes in the distributed data plane. Additionally, an SFCs migration algorithm is designed to optimize the migration cost by deeply analyzing resource allocation in the switch pipeline. Monte has been implemented on both P4 software switches (Bmv2) and hardware switches (Intel Tofino ASIC). Extensive evaluation results show that the migration cost in Monte is 94.03% lower on average than the state-of-the-art deployment scheme, and Monte can effectively save pipeline resources.
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