MuSC: A multi-stage service chains embedding approach. (1st June 2020)

• Record Type: Journal Article
• Authors: El Mensoum, Imane; Wahab, Omar Abdul; Kara, Nadjia; Edstrom, Claes
• Is Part Of: Journal of network and computer applications. Volume 159(2020)
• Publication Date: 2020-06-01
• Subjects: Network function virtualization -- Service function chains -- Virtual functions placement and chaining -- Genetic algorithm -- Chemical reaction optimization; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2020.102593
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Network function virtualization is an emerging concept that is attracting increasing attention in the industry because it offers high levels of agility and flexibility to the network allowing easier software updates, resource adjustment and scalable changes in the configuration of the services. Network functions traditionally delivered on hardware and purpose-built platforms in legacy networks can now be provided through shared virtual resources called VNFs (Virtual network functions) hosted over shared physical network infrastructures. Using network functions as absolute software components would certainly improve the deployment process and the management of the VNF life cycle. Since VNFs are hardware-independent, there is no need to check whether or not a network function is compatible with the rest of the network's physical parts; this also helps reduce the maintenance costs, which can increase drastically in the case of major upgrades to the network infrastructure. Along with all these benefits, shifting to virtual-based networks comes with a significant number of challenges, especially in terms of placing such virtual components, ensuring their interoperability and maintaining the quality of service at a level that is at least as good as what is offered by hardware based architectures. In this paper, we propose a cluster-based placement and chaining solution. The overall proposed approach consists of: 1) formulating an Integer Linear Programming (ILP) model aimed at finding an optimal tradeoff between multiple objective functions that might be sometimes conflicting (e.g hardware resource and energy consumption minimization, transmission delays, bandwidth usage, etc…), 2) classifying the substrate network into a set of on-demand clusters that are efficient for a predefined set of metrics, and 3) using meta-heuristic-based algorithms to find near-optimal solutions for the formulated ILP.