10th EAI International Conference on Performance Evaluation Methodologies and Tools

Research Article

Modeling Security Requirements for VNE algorithms

  • @INPROCEEDINGS{10.4108/eai.25-10-2016.2266673,
        author={Andreas Fischer and Ramona K\'{y}hn and Waseem Mandarawi and Hermann de Meer},
        title={Modeling Security Requirements for VNE algorithms},
        proceedings={10th EAI International Conference on Performance Evaluation Methodologies and Tools},
        publisher={ACM},
        proceedings_a={VALUETOOLS},
        year={2017},
        month={5},
        keywords={virtual network embedding cloud computing security virtual network substrate network network virtualization},
        doi={10.4108/eai.25-10-2016.2266673}
    }
    
  • Andreas Fischer
    Ramona Kühn
    Waseem Mandarawi
    Hermann de Meer
    Year: 2017
    Modeling Security Requirements for VNE algorithms
    VALUETOOLS
    ACM
    DOI: 10.4108/eai.25-10-2016.2266673
Andreas Fischer,*, Ramona Kühn1, Waseem Mandarawi1, Hermann de Meer1
  • 1: University of Passau
*Contact email: andreas.fischer@uni-passau.de

Abstract

Public and private Infrastructure as a Service (IaaS) clouds are widely used by individuals and organizations to provision flexible virtual computing resources on demand. Virtual Network Embedding (VNE) algorithms are employed in this context to provide an automated resource assignment. With multiple involved parties security-aware Virtual Machine (VM) placement becomes highly relevant for production environments. Moreover, VNE algorithms should also consider the security requirements of the interconnections between VMs, thereby extending the problem to networks. This paper discusses security requirements of Virtual Networks (VNs) and shows how they can be modeled in VNE to map them to the provided security mechanisms in the physical network. The paper also presents an implementation of this security-aware VNE model in the public simulation platform ALEVIN, demonstrating the applicability with a realistic use case of such a model.