학술논문

A dynamic pricing algorithm for a network of virtual resources
Document Type
Conference
Source
2016 IEEE NetSoft Conference and Workshops (NetSoft) NetSoft Conference and Workshops (NetSoft), 2016 IEEE. :328-335 Jun, 2016
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Pricing
Heuristic algorithms
IP networks
Noise measurement
Substrates
Cloud computing
Hardware
Language
Abstract
A service chain is a combination of network services (e.g. network address translation (NAT), a firewall, etc.) that are interconnected to support an application (e.g. video-on-demand). Building a service chain requires a set of specialized hardware devices each of which need to be configured with their own command syntax. By moving management functions out of forwarding hardware into controller software, software-defined networking (SDN) simplifies provisioning and reconfiguration of service chains. By moving the network functions out of dedicated hardware devices into software running on standard x86 servers, network function virtualization (NFV) turns the deployment of a service chain into a more (cost)-efficient and flexible process. In an SDN/NFV-based architecture, those service chains are composed of virtual network functions (VNFs) that need to be mapped to physical network components. In literature, several algorithmic approaches exist to do so efficiently and cost-effectively. However, once mapped, a simple revenue model is used for pricing the requested substrate resources. This often leads to a loss of revenue for the infrastructure provider. In this paper, we propose a more advanced, dynamic pricing algorithm for pricing the requested substrate resources. The proposed algorithm increases the infrastructure provider's revenue based on historic data, current infrastructure utilization levels and the pricing of competitors. Our experimental evaluation shows that the proposed algorithm increases the revenue of the infrastructure provider significantly, independent of the average network utilization.