期刊名称:International Journal of Software Engineering and Its Applications
印刷版ISSN:1738-9984
出版年度:2016
卷号:10
期号:7
页码:93-100
DOI:10.14257/ijseia.2016.10.7.09
出版社:SERSC
摘要:Network function virtualization (NFV) virtualizes entire classes of network functions into building blocks of software. A virtualized network function (VNF) can consist of one or more virtual machines to provide communication services. Service Function Chaining (SFC) provides the ability to define an ordered list of virtualized network functions while considering multiple computing constraint conditions such as CPU, memory, and bandwidth. In a cloud data center network, the various virtualized network functions can reside in multiple physical machines and a certain chain of VNFs must be carefully considered to provide an optimal path. Such an optimization problem with multiple constraints is known as an NP-hard optimization problem. We propose a metaheuristic method to provide an optimal chain of VNFs using a genetic algorithm while considering multiple constraints. This paper aims to provide a path with well-balanced computing resources in a cloud data center network environment.