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VNF-DOC: A Dynamic Overload Controller for Virtualized Network Functions in Cloud

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Advanced Information Networking and Applications (AINA 2020)

Abstract

Network Function Virtualization (NFV) supports enterprises and service providers to build reliable network services in a cost-effective way. Such network services are created by combining one or more Virtual Network Functions (VNFs) hosted in private or public cloud infrastructure. However, uncontrolled VNF overload is a major cause of network service failure in NFV. Overload conditions negatively impact throughput, and hence the resiliency requirements of NFV. The ability to detect and mitigate an overload quickly, and ensuring high throughput, for varying overload condition is critical. The existing solutions are unable to meet these combined objectives in VNFs.

In this paper, we propose a Dynamic Overload Controller for VNF (VNF-DOC), which uses VNF’s current and predicted load for every sampling interval, to decide on a mitigation action. It mitigates both transient and sustained overload, by dynamically using cloud auto scale, Virtual Machine buffer pool, and traffic throttling. We evaluate our solution on NFV based IP multimedia system, hosted in the AWS cloud environment. The result shows that VNF-DOC mitigates high capacity overload without any adverse side effects and achieves at least 94% throughput. VNF-DOC is robust in handling varying overload with negligible performance overhead.

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Notes

  1. 1.

    For example, RL=75%, LT1=50%, LT2=75%, LT3=85%, and LT4=90%.

  2. 2.

    We repeated the VNF-DOC experiment three times, with one, two, and three VMs, respectively, in the buffer pool. The study shows that buffer-pool with two VMs provide maximum throughput and higher average performance per VNF.

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Correspondence to Sudhakar Murugasen .

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Murugasen, S., Raman, S., Veezhinathan, K. (2020). VNF-DOC: A Dynamic Overload Controller for Virtualized Network Functions in Cloud. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Advanced Information Networking and Applications. AINA 2020. Advances in Intelligent Systems and Computing, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-44041-1_57

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