Virtual function placement for service chaining with partial orders and anti‐affinity rules. Issue 2 (21st September 2017)

• Record Type: Journal Article
• Authors: Allybokus, Zaid; Perrot, Nancy; Leguay, Jérémie; Maggi, Lorenzo; Gourdin, Eric
• Is Part Of: Networks. Volume 71:Issue 2(2018)
• Page Start: 97
• Page End: 106
• Publication Date: 2017-09-21
• Subjects: software‐defined networking -- network function virtualization -- service function chaining -- anti‐affinity rules -- partial order -- integer linear programming; Network analysis (Planning) -- Periodicals; 658.4032
• DOI: 10.1002/net.21768
• Languages: English
• ISSNs: 0028-3045

Abstract

Abstract : Software‐Defined Networking and Network Function Virtualization are two paradigms that offer flexible software‐based network management. Service providers are instantiating Virtualized Network Functions, for example, firewalls, DPIs, gateways—to highly facilitate the deployment and reconfiguration of network services with reduced time‐to‐value. They use Service Function Chaining technologies to dynamically reconfigure network paths traversing physical and virtual network functions. Providing a cost‐efficient virtual function deployment over the network for a set of service chains is a key technical challenge for service providers, and this problem has recently caught much attention from both Industry and Academia. In this article, we propose a formulation of this problem as an Integer Linear Program that allows one to find the best feasible paths and virtual function placement for a set of services with respect to a total financial cost, while taking into account the (total or partial) order constraints for Service Function Chains of each service and other constraints such as end‐to‐end latency, anti‐affinity rules between network functions on the same physical node and resource limitations in terms of network and processing capacities. Furthermore, we propose a heuristic algorithm based on a linear relaxation of the problem that performs close to optimum for large scale instances. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 71(2), 97–106 2018