Service Broker-Based Architecture Using Multi-Criteria Decision Making for Service Level Agreement

  •  Imane Haddar    
  •  Brahim Raouyane    
  •  Mostafa Bellafkih    


With the on-going trends of the telecom services, the number of service providers with similar functionalities is undergoing a rapid growth. The customers face the difficulty to decide which service provider can satisfy their needs and full their requirements. Negotiating contracts between involved parts, and hiding heterogeneity in the distributed network environment has been challenging for telecom operators and service providers. Different languages exist to describe the Service Level Agreement (SLA), which is a contract between a service provider and a customer. However, since each service provider expresses his SLA in his own way, it disrupts the customer's choice of the best service provider, and leads to a bad contract management. In this respect, we propose a novel architecture for service selection, and SLA management between different stakeholders in our network architecture. The idea is to set up a smart broker where we implemented a Multi-Criteria Decision Making (MCDM) method to maximize utility function so that the customer can choose services with required QoS performances. We also came up with the idea of settling a negotiation model for the SLA, and a context based SLA contract ontology in IP Multimedia Subsystem (IMS) network is also proposed to provide users with a clear model to express their requirements and preferences. Moreover, we used the New Generation Operations Systems and Software (NGOSS) Framework to model and analyze networks and services actions. To better understand the relationship and the projection of NGOSS Framework and IMS platform, we introduce an SLA management and monitoring architecture in IMS network.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

Journal Metrics

WJCI (2020): 0.439

Impact Factor 2020 (by WJCI): 0.247

Google Scholar Citations (March 2022): 6907

Google-based Impact Factor (2021): 0.68

h-index (December 2021): 37

i10-index (December 2021): 172

(Click Here to Learn More)