Scalable Cost-Efficient Placement and Chaining of Virtual Network Functions

  • Marcelo Caggiani Luizelli
  • Luciana Salete Buriol
  • Luciano Paschoal Gaspary


While Network Function Virtualization (NFV) is increasingly gaining momentum, with promising benefits of flexible service function deployment and reduced operations and management costs, there are several challenges that remain to be properly tackled, so that it can realize its full potential. One of these challenges, which has a significant impact on the NFV production chain, is effectively and (cost) efficiently deploying service functions, while ensuring that service level agreements are satisfied and making wise allocations of network resources. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement chaining of virtual network functions (VNFs) - a key feature for the effective success of NFV. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. We formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose a mathematical model to solve it. Our model has established one of the first baseline comparison in the field of resource management in NFV and has been widely used in the recent literature. We also address scalability of VNFPC problem to solve large instances by proposing a novel fix-and-optimize-based heuristic algorithm for tackling it. Further, we extensively measure the performance limitations of realistic NFV deployments. Based on that, we propose an analytical model that accurately predict incurred operational costs. Then, we develop an optimal Intra-datacenter service chain deployment mechanism based on our cost model. Finally, we tackle the problem of monitoring service chains in NFV-based environments efficiently.

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LUIZELLI, Marcelo Caggiani; BURIOL, Luciana Salete; GASPARY, Luciano Paschoal. Scalable Cost-Efficient Placement and Chaining of Virtual Network Functions. In: CONCURSO DE TESES E DISSERTAÇÕES (CTD), 31. , 2018, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2018 . ISSN 2763-8820. DOI: