IEEE Access (Jan 2019)

Cost Efficient and Low-Latency Network Service Chain Deployment Across Multiple Domains for SDN

  • Chuangchuang Zhang,
  • Xingwei Wang,
  • Yong Zhao,
  • Anwei Dong,
  • Fuliang Li,
  • Min Huang

DOI
https://doi.org/10.1109/ACCESS.2019.2944874
Journal volume & issue
Vol. 7
pp. 143454 – 143470

Abstract

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With the fast development of Internet, network traffic rapidly grows and the size of Internet scale gradually becomes bigger. It brings serious challenges to Network Service Chain (NSC) deployment across multiple domains which are managed by different network operators and service providers. It is difficult for each server in the multi-domain network to obtain a global topology view and available resource information of other domains. Meanwhile, there exist various operational strategies for different network operators and service providers in the multi-domain network. How to optimally deploy NSCs in a multi-domain network to realize cost efficient and low latency service provisioning is challenging. To this end, in this paper, we study the problem of NSC deployment across multiple domains. Specifically, by leveraging Software Defined Networking (SDN) architecture, we present a novel service deployment framework to deploy Virtual Network Functions (VNFs) in the multi-domain network in a cost efficient and low latency method. Then, we establish a multi-objective optimization model with the target of minimizing end-to-end delay, service cost and operational cost with the constraints of resource allocation and VNF dependency relationships. Furthermore, we design a novel heuristic NSC deployment algorithm to solve the optimization model. In the proposed heuristic algorithm, VNF dependency relationship based NSC processing workflow optimization method and Dijkstra algorithm based NSC deployment adjustment method are presented to optimize delay and cost. Finally, extensive simulations demonstrate that the proposed heuristic deployment algorithm is efficient and outperforms comparison algorithms in terms of end-to-end delay, service cost and operational cost.

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