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Specification, composition, and placement of network services with flexible structures
Author(s) -
Dräxler Sevil,
Karl Holger
Publication year - 2017
Publication title -
international journal of network management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.373
H-Index - 28
eISSN - 1099-1190
pISSN - 1055-7148
DOI - 10.1002/nem.1963
Subject(s) - computer science , flexibility (engineering) , service (business) , orchestration , distributed computing , heuristic , network service , service composition , software , function (biology) , services computing , set (abstract data type) , pareto principle , computer network , web service , quality of service , mathematical optimization , operating system , world wide web , artificial intelligence , art , musical , statistics , mathematics , economy , evolutionary biology , economics , visual arts , biology , programming language
Summary Network function virtualization and software‐defined networking allow services consisting of virtual network functions to be designed and implemented with great flexibility by facilitating automatic deployments, migrations, and reconfigurations for services and their components. For extended flexibility, we go beyond seeing services as a fixed chain of functions. We define the service structure in a flexible way that enables changing the order of functions in case the functionality of the service is not influenced by this and propose a YANG data model for expressing this flexibility. Flexible structures allow the network orchestration system to choose the optimal composition of service components that, for example, gives the best results for placement of services in the network. When number of flexible services and number of components in each service increase, combinatorial explosion limits the practical use of this flexibility. In this paper, we describe a selection heuristic that gives a Pareto set of the possible compositions of a service as well as possible combinations of different services, with respect to different optimization objectives. Moreover, we present a heuristic algorithm for placement of a combination of services, which aims at placing service components along shortest paths that have enough capacity for accommodating the services. By applying these solutions, we show that allowing flexibility in the service structure is feasible.