A hierarchical control plane framework for integrated SDN-SFC Management in Multi-tenant Cloud Data Centers

Lakshmi, BS and Lakshmi, J (2020) A hierarchical control plane framework for integrated SDN-SFC Management in Multi-tenant Cloud Data Centers. In: IEEE International Conference on Cloud Computing, CLOUD, 18-24 October 2020, Virtual, Beijing; China, pp. 258-266.

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Abstract

Service Functions have become a prominent part of cloud data center networks. Providing qualitative services to the hosted applications, the provision and management of service function chain components require an autonomous and reactive management framework that can respond to the dynamics of network state and application requirements. While software defined network controllers enable programmable network configuration, current implementations do not extend its capability to manage service function chains. Hence, a common network control entity that manages not only forwarding devices, but also the service function chain components is required. With a global view of the network which includes the service functions, the integrated controller can make network configuration decisions that are globally optimized. However, this integration gives rise to the problems of controller scalability and multi-tenancy management. To this end, this paper proposes a hierarchical controller framework for software defined network controller integrated with service function chain management that addresses both these problems in cloud data centers. The proposed controller is implemented and evaluated over a simulated data center network, and a comparative evaluation is made with existing controller architectures. The proposed controller is observed to reduce packet loss by 19.81 and 9.37 in comparison to centralized and distributed controller frameworks with integrated SFC management, respectively. Also, while the centralized controller gives the least flow setup times for smaller number of tenants, beyond 70 tenants the proposed hierarchical controller gives the least flow setup times. © 2020 IEEE.

Item Type:	Conference Paper
Publication:	IEEE International Conference on Cloud Computing, CLOUD
Publisher:	IEEE Computer Society
Additional Information:	cited By 0; Conference of 13th IEEE International Conference on Cloud Computing, CLOUD 2020 ; Conference Date: 18 October 2020 Through 24 October 2020; Conference Code:165943
Department/Centre:	Division of Interdisciplinary Sciences > Computational and Data Sciences Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	27 Jan 2021 05:22
Last Modified:	27 Jan 2021 05:22
URI:	http://eprints.iisc.ac.in/id/eprint/67839

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