An economic framework for analysis of network architectures: SDN and MPLS cases


Karakus M., Durresi A.

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, cilt.136, ss.132-146, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 136
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1016/j.jnca.2019.02.032
  • Dergi Adı: JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.132-146
  • Anahtar Kelimeler: SDN, Economics, Price, Cost, CAPEX, OPEX, SOFTWARE-DEFINED NETWORKING, SCALABILITY, ALGORITHM
  • Ankara Üniversitesi Adresli: Hayır

Özet

As new networking architectures such as 5G start materializing in the next era of communication revolution, economic and operational facets of these future networks drive researchers to rethink about their capabilities of flexibility, agility, programmability, and cost-effectiveness. These are the main features to make networks like 5G (fifth-generation) possible and available for societies shortly because they are the fundamental catalysts to achieve economic success in a network. It is vital for network owners to analyze and understand economic aspects of a network architecture before deciding to invest in it. In this article, we introduce a framework utilizing an activity-based approach for the techno-economic analysis of network architectures. In particular, we perform an economic analysis of SDN (Software Defined Networking) technology and MPLS (Multiprotocol Label Switching) technology in order to understand how programmable networking, i.e., SDN technology, affects the network economics compared to traditional networking, i.e., MPLS technology. To this end, we firstly conduct a quantitative analysis exploiting an activity-based approach for CAPEX (Capital Expenditure) and OPEX (Operational Expenditure) calculations of a network. Secondly, we evaluate the architectures above concerning their economic performances using two metrics: Unit Service Cost Scalability metric and Cost-to-Service metric. Also, we present mathematical models to calculate certain cost parts of a network. Also, we compare different popular SDN control plane models, Centralized Control Plane (CCP), Distributed Control Plane (DCP), and Hierarchical Control Plane (HCP), to understand their economic impact with regards to the defined metrics. We use video as the service with different traffic patterns for the comparison. This work aims at being a useful primer to providing insights regarding which technology and control plane model(s) are appropriate for a specific service, i.e., video, for network owners to plan their investments.